Pursuant to Local Laws 126, 127, and 128 of 2016, certain demographic data is collected voluntarily and anonymously by persons voluntarily seeking social services. This data can be used by agencies and the public to better understand the demographic makeup of client populations and to better understand and serve residents of all backgrounds and identities. The data presented here has been collected through either electronic form or paper surveys offered at the point of application for services. These surveys are anonymous. Each record represents an anonymized demographic profile of an individual applicant for social services, disaggregated by response option, agency, and program. Response options include information regarding ancestry, race, primary and secondary languages, English proficiency, gender identity, and sexual orientation. Idiosyncrasies or Limitations: Note that while the dataset contains the total number of individuals who have identified their ancestry or languages spoke, because such data is collected anonymously, there may be instances of a single individual completing multiple voluntary surveys. Additionally, the survey being both voluntary and anonymous has advantages as well as disadvantages: it increases the likelihood of full and honest answers, but since it is not connected to the individual case, it does not directly inform delivery of services to the applicant. The paper and online versions of the survey ask the same questions but free-form text is handled differently. Free-form text fields are expected to be entered in English although the form is available in several languages. Surveys are presented in 11 languages. Paper Surveys 1. Are optional 2. Survey taker is expected to specify agency that provides service 2. Survey taker can skip or elect not to answer questions 3. Invalid/unreadable data may be entered for survey date or date may be skipped 4. OCRing of free-form tet fields may fail. 5. Analytical value of free-form text answers is unclear Online Survey 1. Are optional 2. Agency is defaulted based on the URL 3. Some questions must be answered 4. Date of survey is automated

Abstract

The 2006-07 Pakistan Demographic and Health Survey (PDHS) was undertaken to address the monitoring and evaluation needs of maternal and child health and family planning programmes. The survey was designed with the broad objective to provide policymakers, primarily in the Ministries of Population Welfare and Health, with information to improve programmatic interventions based on empirical evidence. The aim is to provide reliable estimates of the maternal mortality ratio (MMR) at the national level and a variety of other health and population indicators at national, urban-rural, and provincial levels.

The 2006-07 Pakistan Demographic and Health Survey (PDHS) is the fifth in a series of demographic surveys conducted by the National Institute of Population Studies (NIPS) since 1990. However, the PDHS 2006-07 is the second survey conducted as part of the worldwide Demographic andHealth Surveys programme. The survey was conducted under the aegis of the Ministry of Population Welfare and implemented by the National Institute of Population Studies. Other collaborating institutions include the Federal Bureau of Statistics, the Aga Khan University, and the National Committee for Maternal and Neonatal Health. Technical support was provided by Macro International Inc. and financial support was provided by the United States Agency for International Development (USAID). The United Nations Population Fund (UNFPA) and United Nations Children's Fund (UNICEF) provided logistical support for monitoring the fieldwork for the PDHS.

The 2006-07 PDHS supplements and complements the information collected through the censuses and demographic surveys conducted by the Federal Bureau of Statistics. It updates the available information on population and health issues, and provides guidance in planning, implementing, monitoring and evaluating health and population programmes in Pakistan. Some of the findings of the PDHS may seem at variance with data compiled by other sources. This may be due to differences in methodology, reference period, wording of questions and subsequent interpretation. This fact may be kept in mind while analyzing and comparing PDHS data with other sources. The results of the survey assist in the monitoring of the progress made towards meeting the Millennium Development Goals (MDGs).

The 2006-07 PDHS includes topics related to fertility levels and determinants, family planning, fertility preferences, infant, child and maternal mortality and their causes, maternal and child health, immunization and nutritional status of mothers and children, knowledge of HIV/AIDS, and malaria. The 2006-07 PDHS also includes direct estimation of maternal mortality and its causes at the national level for the first time in Pakistan. The survey provides all other estimates for national, provincial and urban-rural domains. This being the fifth survey of its kind, there is considerable trend information on reproductive health, fertility and family planning over the past one and a half decades.

More specifically, PDHS had the following objectives: - Collect quality data on fertility levels and preference, family planning knowledge and use, childhood—and especially neonatal—mortality levels and awareness regarding HIV/ AIDS and other indicators relevant to the Millennium Development Goals and the Poverty Reduction Strategy Paper; - Produce a reliable national estimate of the MMR for Pakistan, as well as information on the direct and indirect causes of maternal deaths using verbal autopsy instruments; - Investigate factors that impact on maternal and neonatal morbidity and mortality (i.e., antenatal and delivery care, treatment of pregnancy complications, and postnatal care); - Improve the capacity of relevant organizations to implement surveys and analyze and disseminate survey findings.

Geographic coverage

The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain).

The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA.

In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities.

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

The 2006-07 PDHS is the largest-ever household based survey conducted in Pakistan. The sample is designed to provide reliable estimates for a variety of health and demographic variables for various domains of interest. The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain). One of the main objectives of the 2006-07 Pakistan Demographic and Health Survey (PDHS) is to provide a reliable estimate of the maternal mortality ratio (MMR) at the national level. In order to estimate MMR, a large sample size was required. Based on prior rough estimates of the level of maternal mortality in Pakistan, a sample of about 100,000 households was proposed to provide estimates of MMR for the whole country. For other indicators, the survey is designed to produce estimates at national, urban-rural, and provincial levels (each as a separate domain). The sample was not spread geographically in proportion to the population; rather, the smaller provinces (e.g., Balochistan and NWFP) as well as urban areas were over-sampled. As a result of these differing sample proportions, the PDHS sample is not self-weighting at the national level.

The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA.

In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities. Each of these cities constitutes a stratum, which has further been substratified into low, middle, and high-income groups based on the information collected during the updating of the urban sampling frame. After excluding the population of large-sized cities from the population of respective former administrative divisions, the remaining urban population within each of the former administrative divisions of the four provinces was grouped together to form a stratum.

In rural areas, each district in Punjab, Sindh, and NWFP provinces is considered as an independent stratum. In Balochistan province, each former administrative division has been treated as a stratum. The survey adopted a two-stage, stratified, random sample design. The first stage involved selecting 1,000 sample points (clusters) with probability proportional to size-390 in urban areas and 610 in rural areas. A total of 440 sample points were selected in Punjab, 260 in Sindh, 180 in NWFP, 100 in Balochistan, and 20 in FATA. In urban areas, the sample points were selected from a frame maintained by the FBS, consisting of 26,800 enumeration blocks, each including about 200-250 households. The frame for rural areas consists of the list of 50,588 villages/mouzas/dehs enumerated in the 1998 population census.

The FBS staff undertook the task of a fresh listing of the households in the selected sample points. Aside from 20 sample points in FATA, the job of listing of households could not be done in four areas of Balochistan due to inability of the FBS to provide household listings because of unrest in those areas. Another four clusters in NWFP could not be covered because of resistance and refusal of the community. In other words, the survey covered a total of 972 sample points.

The second stage of sampling involved selecting households. In each sample point, 105 households were selected by applying a systematic random sampling technique. This way, a total of 102,060 households were selected. Out of 105 sampled households, ten households in each sample point were selected using a systematic random sampling procedure to conduct interviews for the Long Household and the Women's Questionnaires. Any ever-married woman aged 12-49 years who was a usual resident of the household or a visitor in the household who stayed there the night before the survey was eligible for interview.

Mode of data collection

Face-to-face

Research instrument

The following six types of questionnaires were used in the PDHS: - Community Questionnaire - Short Household Questionnaire - Long Household Questionnaire - Women’s Questionnaire - Maternal Verbal Autopsy Questionnaire - Child Verbal Autopsy Questionnaire

The contents of the Household and Women’s Questionnaires were based on model questionnaires developed by the MEASURE DHS programme, while the Verbal Autopsy Questionnaires were developed by Pakistani experts and the Community Questionnaire was patterned on the basis of one used by NIPS in previous surveys.

NIPS developed the draft questionnaires in consultation with a broad spectrum of technical experts, government agencies, and local and international organizations so as to reflect relevant issues of population, family planning, HIV/AIDS, and other health areas. A number of meetings were organized

Template for Participant demographics.

Abstract

The Jordan Population and Family Health Survey (JPFHS) is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 2012 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, and fertility preferences, as well as maternal and child health and nutrition, that can be used by program managers and policymakers to evaluate and improve existing programs. The JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The 2012 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and for the two special domains: the Badia areas and people living in refugee camps. To facilitate comparisons with previous surveys, the sample was also designed to produce estimates for the three regions (North, Central, and South). The grouping of the governorates into regions is as follows: the North consists of Irbid, Jarash, Ajloun, and Mafraq governorates; the Central region consists of Amman, Madaba, Balqa, and Zarqa governorates; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba governorates.

The 2012 JPFHS sample was selected from the 2004 Jordan Population and Housing Census sampling frame. The frame excludes the population living in remote areas (most of whom are nomads), as well as those living in collective housing units such as hotels, hospitals, work camps, prisons, and the like. For the 2004 census, the country was subdivided into convenient area units called census blocks. For the purposes of the household surveys, the census blocks were regrouped to form a general statistical unit of moderate size (30 households or more), called a "cluster", which is widely used in surveys as a primary sampling unit (PSU).

Stratification was achieved by first separating each governorate into urban and rural areas and then, within each urban and rural area, by Badia areas, refugee camps, and other. A two-stage sampling procedure was employed. In the first stage, 806 clusters were selected with probability proportional to the cluster size, that is, the number of residential households counted in the 2004 census. A household listing operation was then carried out in all of the selected clusters, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. In the second stage of selection, a fixed number of 20 households was selected in each cluster with an equal probability systematic selection. A subsample of two-thirds of the selected households was identified for anthropometry measurements.

Refer to Appendix A in the final report (Jordan Population and Family Health Survey 2012) for details of sampling weights calculation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 JPFHS used two questionnaires, namely the Household Questionnaire and the Woman’s Questionnaire (see Appendix D). The Household Questionnaire was used to list all usual members of the sampled households, and visitors who slept in the household the night before the interview, and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of the household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and the availability of durable goods. Moreover, the questionnaire included questions about child discipline. The Household Questionnaire was also used to identify women who were eligible for the individual interview (ever-married women age 15-49 years). In addition, all women age 15-49 and children under age 5 living in the subsample of households were eligible for height and weight measurement and anemia testing.

The Woman’s Questionnaire was administered to ever-married women age 15-49 and collected information on the following topics: • Respondent’s background characteristics • Birth history • Knowledge, attitudes, and practice of family planning and exposure to family planning messages • Maternal health (antenatal, delivery, and postnatal care) • Immunization and health of children under age 5 • Breastfeeding and infant feeding practices • Marriage and husband’s background characteristics • Fertility preferences • Respondent’s employment • Knowledge of AIDS and sexually transmitted infections (STIs) • Other health issues specific to women • Early childhood development • Domestic violence

In addition, information on births, pregnancies, and contraceptive use and discontinuation during the five years prior to the survey was collected using a monthly calendar.

The Household and Woman’s Questionnaires were based on the model questionnaires developed by the MEASURE DHS program. Additions and modifications to the model questionnaires were made in order to provide detailed information specific to Jordan. The questionnaires were then translated into Arabic.

Anthropometric data were collected during the 2012 JPFHS in a subsample of two-thirds of the selected households in each cluster. All women age 15-49 and children age 0-4 in these households were measured for height using Shorr height boards and for weight using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children in the field to measure their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Cleaning operations

Fieldwork and data processing activities overlapped. Data processing began two weeks after the start of the fieldwork. After field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman, where they were registered and stored. Special teams were formed to carry out office editing and coding of the openended questions.

Data entry and verification started after two weeks of office data processing. The process of data entry, including 100 percent reentry, editing, and cleaning, was done by using PCs and the CSPro (Census and Survey Processing) computer package, developed specially for such surveys. The CSPro program allows data to be edited while being entered. Data processing operations were completed by early January 2013. A data processing specialist from ICF International made a trip to Jordan in February 2013 to follow up on data editing and cleaning and to work on the tabulation of results for the survey preliminary report, which was published in March 2013. The tabulations for this report were completed in April 2013.

Response rate

In all, 16,120 households were selected for the survey and, of these, 15,722 were found to be occupied households. Of these households, 15,190 (97 percent) were successfully interviewed.

In the households interviewed, 11,673 ever-married women age 15-49 were identified and interviews were completed with 11,352 women, or 97 percent of all eligible women.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2012 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2012 JPFHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012 JPFHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer

The City of Norfolk is committed to using data to inform decisions and allocate resources. An important source of data is input from residents about their priorities and satisfaction with the services we provide. Norfolk last conducted a citywide survey of residents in 2022.

To provide up-to-date information regarding resident priorities and satisfaction, Norfolk contracted with ETC Institute to conduct a survey of residents. This survey was conducted in May and June 2024; surveys were sent via the U.S. Postal Service, and respondents were given the choice of responding by mail or online. This survey represents a random and statistically valid sample of residents from across the city, including each Ward. ETC Institute monitored responses and followed up to ensure all sections of the city were represented. Additionally, an opportunity was provided for residents not included in the random sample to take the survey and express their views. This dataset includes all random sample survey data including demographic information; it excludes free-form comments to protect privacy. It is grouped by Question Category, Question, Response, Demographic Question, and Demographic Question Response. This dataset will be updated every two years.

this form described the socio demographic characteristics of the participants

A random sample of households were invited to participate in this survey. In the dataset, you will find the respondent level data in each row with the questions in each column. The numbers represent a scale option from the survey, such as 1=Excellent, 2=Good, 3=Fair, 4=Poor. The question stem, response option, and scale information for each field can be found in the var "variable labels" and "value labels" sheets. VERY IMPORTANT NOTE: The scientific survey data were weighted, meaning that the demographic profile of respondents was compared to the demographic profile of adults in Bloomington from US Census data. Statistical adjustments were made to bring the respondent profile into balance with the population profile. This means that some records were given more "weight" and some records were given less weight. The weights that were applied are found in the field "wt". If you do not apply these weights, you will not obtain the same results as can be found in the report delivered to the Bloomington. The easiest way to replicate these results is likely to create pivot tables, and use the sum of the "wt" field rather than a count of responses.

Abstract

The 2009 MDHS was designed to provide data to monitor the population and health situation in Maldives. Specifically, the MDHS collected information on fertility levels and preferences, marriage, sexual activity, knowledge and use of family planning methods, breastfeeding practices, nutrition status of women and young children, childhood mortality, maternal and child health, and awareness and behaviour regarding AIDS and other sexually transmitted infections. At the household level, the survey collected information on domains of physical disability among those age 5 and older, developmental disability among young children, support for early learning, children at work, the impact of the tsunami of 2004, health expenditures, and care and support for physical activity of adults age 65 and older. At the individual level, the survey assessed additional features of blood pressure, diabetes, heart attack, and stroke.

Geographic coverage

National

Analysis unit

• Households
• Children age under 5
• Women age 15-49
• Men age 15-64

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The population of the republic of Maldives is distributed on 195 inhabited islands among a total of 202 inhabited islands; seven islands have no residents (MPND, 2008). Each inhabited island is an administrative unit with an island office that handles island-based affairs. The islands are regrouped to form atolls, a higher-level administrative unit with an atoll office and an atoll chief. There are 20 atolls in total in the republic. The capital city of Malé and the two surrounding islands, Villingili and Hulhumale, form a special atoll. The 21 atolls are regrouped to form six geographic regions according to their location. Malé atoll alone forms a region. In Maldives, there is no urbanrural designation for residential households within an atoll. All residential households in the 20 atolls outside of Malé are considered rural; all residential households in Malé are considered urban.

The 2009 Maldives DHS is based on a probability sample of 7,515 households. The sample was designed to produce representative data on households, women, and children for the country as a whole, for urban and rural areas, for the six geographical regions, and for each of the atolls of the country. The male and youth surveys were designed to produce representative results for the country as a whole, for urban and rural areas, and for each of the six geographical regions.

The 2006 Maldives Population and Housing Census provided the sampling frame for the 2009 MDHS. The MDHS sample was a stratified multistage sample selected in two stages from the census frame. In the first stage, 270 census blocks were selected using a systematic selection, with probability proportional to the number of residential households residing in the block. Stratification was achieved by treating each of the 21 atolls as a sampling stratum. Samples were selected independently in each stratum according to an appropriate allocation.

In the second stage of sampling, residential households were selected in each of the selected census blocks. Household selection involved an equal probability systematic selection of a fixed number of households: 28 households per block. Households were selected from the household listings created in the census, but to allow all households an opportunity to be included in the sample, listings were sent to island offices for updating prior to making household selections for the MDHS.

All ever-married women age 15-49 in the total sample of MDHS households, who were either usual residents of the household or visitors present in the household on the night before the survey, were eligible to be interviewed. In half of the households selected for the ever-married sample of women, all ever-married men age 15-64, who were either usual residents of the household or visitors present in the household on the night before the survey, were eligible to be interviewed. In the same half of households selected for the ever-married sample of men, never-married women and nevermarried men age 15-24, who were either usual residents of the household or visitors present in the household on the night before the survey, were also eligible to be interviewed. The MDHS was for the most part limited to Maldivian citizens; non-Maldivians were included in the survey only if they were the spouse, son, or daughter of a Maldivian.

Note: See detailed sample implementation information in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

Four questionnaires were used for the 2009 MDHS: the Household Questionnaire, the Women’s Questionnaire, the Men’s Questionnaire, and the Youth Questionnaire. The contents of the Household, Women’s, and Men’s questionnaires were based on model questionnaires developed by the MEASURE DHS programme. The DHS model questionnaires were modified to reflect concerns pertinent to the Maldives in the areas of population, women and children’s health, family planning, and others. Questionnaires were translated from English into Dhivehi.

The Household Questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Basic information was collected on the characteristics of each person listed, including their age, sex, education, and relationship to the head of the household. The Household Questionnaire was also designed to collect information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, water shortage, materials used for the floor and roof of the house, and ownership of various durable goods. In addition, height and weight measurements of ever-married women age 15-49 and children age 6-59 months were recorded in the Household Questionnaire to assess their nutritional status.

Topics added to the Household Questionnaire to reflect issues relevant in the Maldives include physical disability among those age 5 and older, developmental disability among young children, support for early learning, children at work, the tsunami of 2004, health expenditures, and care and support for physical activities of adults age 65 and older.

The Women’s Questionnaire was used to collect information from ever-married women age 15-49. These women were asked questions on the following topics: - Background characteristics (education, media exposure, etc.) - Reproductive history - Knowledge and use of family planning methods - Fertility preferences - Antenatal and delivery care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant and child feeding practices - Childhood mortality - Awareness and behaviour about AIDS and other sexually transmitted infections (STIs) - Knowledge of blood pressure, diabetes, heart attack, and stroke

The Men’s Questionnaire was administered to all ever-married men age 15-64 living in every second household in the MDHS sample. The Men’s Questionnaire collected much of the same information as the Women’s Questionnaire, but it was shorter because it did not contain questions on reproduction, maternal and child health, and nutrition.

The Youth Questionnaire was administered to all never-married women and men age 15-24 living in every second household in the MDHS sample (the same one-half selected for the Men’s survey). The Youth Questionnaire focuses on priorities of the MOHF that pertain to young adults: reproductive health, knowledge and attitudes about HIV/AIDS, sexual activity, and tobacco, alcohol, and drug use.

Response rate

A total of 7,515 households were selected in the sample, of which 7,137 were found to be occupied at the time of data collection. The difference between the number of households selected and the number occupied usually occurs because some structures are found to be vacant or non-existent. The number of occupied households successfully interviewed was 6,443, yielding a household response rate of 90 percent.

In the households interviewed in the survey, a total of 8,362 ever-married women were identified as eligible for the individual interview; interviews were completed with 7,131 women, yielding a female response rate of 85 percent. In the one-half sub-sample of MDHS households, a total of 3,224 evermarried men age 15-64 were identified as eligible for the individual interview; interviews were completed with 1,727 men, yielding a male response rate of 54 percent. In the same sub-sample of households, a total of 3,205 never-married women and men age 15-24 (youth) were identified as eligible for individual interview; interviews were completed with 2,240 youth, yielding a youth response rate of 70 percent. The response rate was higher for female youth (80 percent) than male youth (61 percent).

The urban household response rate of 83 percent is lower than the 92 percent response rate among rural households. The same is true for individual interviews with ever-married respondents; response rates are somewhat lower among urban women (79 percent) and men (47 percent) than among their rural counterparts (87 percent and 55 percent, respectively). The difference in response rates between urban and rural youth is negligible.

Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling

We illustrate the utility of expert elicitation, explicit recognition of uncertainty, and the value of information for directing management and research efforts for invasive species, using tegu lizards (Salvator merianae) in southern Florida as a case study. We posited a post-birth pulse, matrix model, which was parameterized using a 3-point process to elicit estimates of tegu demographic rates from herpetology experts. We fit statistical distributions for each parameter and for each expert, then drew and pooled a large number of replicate samples from these to form a distribution for each demographic parameter. Using these distributions, we generated a large sample of matrix models to infer how the tegu population might respond to control efforts. We used the concepts of Pareto efficiency and stochastic dominance to conclude that targeting older age classes at relatively high rates appears to have the best chance of minimizing tegu abundance and control costs. Expert opinion combined with an explicit consideration of uncertainty can be valuable for conducting an initial assessment of the effort needed to control the invader. The value of information can be used to focus research in a way that not only helps increases the efficacy of control, but minimizes costs as well.

Abstract

The 2013 Liberia Demographic and Health Survey (LDHS) is designed to provide data for monitoring the population and health situation in Liberia. The 2013 LDHS is the fourth Demographic and Health Survey conducted in Liberia since 1986. The primary objective of the 2013 LDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2013 LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, and HIV/AIDS and other sexually transmitted infections (STIs). In addition, the 2013 LDHS provides estimates on HIV prevalence among adult Liberians.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual/ person
• Children age 0-5 years
• Woman age 15 to 49 years
• Man age 15 to 49 years

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sampling frame for the 2013 LDHS was developed by the Liberia Institute of Statistics and Geo-Information Services (LISGIS) after the 2008 National Population and Housing Census (NPHC). The sampling frame is similar to that used for the 2009 and 2011 Liberia Malaria Indicator Surveys (LMIS), except that the classification of localities as urban or rural was updated through the application of standardized definitions. The sampling frame excluded nomadic and institutional populations such as residents of hotels, barracks, and prisons. Notably, the sampling frame for the 2013 LDHS differs markedly from that used for the 2007 LDHS, which was based on the 1984 NPHC. Taken together, these differences may complicate data comparisons between surveys.

The 2013 LDHS followed a two-stage sample design that allowed estimates of key indicators for the country as a whole, for urban and rural areas separately, for Greater Monrovia and other urban areas separately, and for each of 15 counties. To facilitate estimates of geographical differentials for certain demographic indicators, the 15 counties were collapsed into five regions as follows: North Western: Bomi, Grand Cape Mount, and Gbarpolu South Central: Montserrado, Margibi, and Grand Bassa South Eastern A: River Cess, Sinoe, and Grand Gedeh South Eastern B: River Gee, Grand Kru, and Maryland North Central: Bong, Nimba, and Lofa

Regional data were presented in the 2007 LDHS, the 2009 LMIS, and the 2011 LMIS. However, in contrast with these past surveys, the South Central region now includes Monrovia. Thus, data presented for the South Central region in this report is not directly comparable to that presented in the 2007 LDHS, the 2009 LMIS, or the 2011 LMIS.

The first stage of sample selection involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2008 NPHC. Overall, the sample included 322 sample points, 119 in urban areas and 203 in rural areas. To allow for separate estimates of Greater Monrovia and Montserrado as a whole, 44 sample points were selected in Montserrado; 16 to 26 sample points were selected in each of the other 14 counties.

The second stage of selection involved the systemic sampling of households. A household listing operation was undertaken in all the selected EAs from mid-September to mid-October 2012. From these lists, households to be included in the survey were selected. Approximately 30 households were selected from each sample point for a total sample size of 9,677 households. During the listing, geographic coordinates (latitude and longitude) were taken in the center of the populated area of each EA using global positioning system (GPS) units.

Because of the approximately equal sample sizes in each region, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the households, all men age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In the subsample of households selected for the male survey, blood samples were collected for laboratory testing to detect HIV from eligible women and men who consented; in this same subsample of households, height and weight information was collected from eligible women, men, and children 0-59 months.

Further details on the sample design and implementation are given in Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2013 LDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires are based on MEASURE DHS standard survey questionnaires and were adapted to reflect the population and health issues relevant to Liberia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors.

Given that there are dozens of local languages in Liberia, most of which have no accepted written script and are not taught in the schools, and given that English is widely spoken, it was decided not to attempt to translate the questionnaires into vernaculars. However, many of the questions were broken down into a simpler form of Liberian English that interviewers could use with respondents.

The Household Questionnaire was used to list all the usual members of and visitors to selected households. Some basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interview and HIV testing. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facility, materials used for the floor of the house, ownership of various durable goods, ownership and use of mosquito nets, and information on household out-of-pocket health-related expenditures. The Household Questionnaire was also used to record height and weight measurements of children 0-59 months and eligible adults. Also recorded was whether or not eligible adults consented to HIV testing.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49.

The Man’s Questionnaire was administered to all men age 15-49 in the subsample of households selected for the male survey in the 2013 LDHS sample. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health.

Cleaning operations

All questionnaires were returned to the LISGIS central office in Monrovia for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer-identified errors. The data were processed by a team of 12 data entry clerks, two data editors, one data entry supervisor, and two administrators of questionnaires; the latter checked that the clusters were completed according to the sample selection and that all members of the household eligible for individual interview were identified. Secondary editing was led by an LDHS coordinator. Several LISGIS staff took on the responsibility of receiving the blood samples from the field and checking them before sending them to the Montserrado Regional Blood Bank for storage. Data entry and editing using CSPro software was initiated in April 2013 and completed in late August 2013.

Response rate

A total of 9,677 households were selected for the sample, of which 9,386 were occupied. Of the occupied households, 9,333 were successfully interviewed, yielding a response rate of 99 percent.

In the interviewed households, 9,462 eligible women were identified for individual interview; of these, complete interviews were conducted with 9,239 women, yielding a response rate of 98 percent. In the subsample of households selected for the male survey, 4,318 eligible men were identified and 4,118 were successfully interviewed, yielding a response rate of 95 percent. The lower response rate for men was likely due to their more frequent and longer absences from the household.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2013 Liberia Demographic and Health Survey to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2013 LDHS is only one of many samples that could have been selected from the same population,

Abstract

To improve the situation the PCBS has decided to undertake a fairly large demographic survey The main purpose of this survey is to provide basic demographic estimates at both the national and district level filling important gaps in existing statistics and reducing uncertainties surrounding the utility of available data Specifically, the survey provides detailed data on the following topics Population structure Female fertility Fertility preference Infant and child mortality Maternal and adult mortality Internal and international migration Marriage Family and household composition Educational attainmentHousing conditions

Geographic coverage

The target population consists of all Palestinian households that usually reside in the West Bank and Gaza Strip

Analysis unit

individual/ Household

Universe

The target population in this sample survey comprises all households living in West Bank and Gaza Strip excluding institutional population and nomads

Kind of data

Sample survey data [ssd]

Sampling procedure

A sampling strategy comprises two main elements: a sample design describing the scheme by which the sample of survey units is selected, and the estimators by which survey results can be computed from sample data. The two elements are usually closely interrelated, and determine the quality or reliability of survey estimates. In this section both elements will be described briefly. A more detailed description is provided in a separate working paper (Abu Hassan and Tamsfoss 1995).

The sample design adopted is a stratified three stage design for selection of households to be surveyed. At the first stage a sample of localities was selected. The sample localities have been subdivided into cells of approximately equal size, and a number of cells were selected randomly from each of the sample localities at the second stage. At the third and final stage, a sample of households was selected from the sample cells. For all the demographic variables included in the survey, records were taken for all members of the sample household.

Although a two-stage design would have been preferable, the present, more complex one is partly an outcome of limited availability of data on which sample designing usually is based, specifically data on the population size of various small area units, e.g. cells. The sample designing was undertaken in parallel with the updating of maps for the localities in the West Bank and Gaza Strip during the winter and spring 1995 - another ongoing PCBS project. Due to the limited time available, the design had to be completed before a complete set of updated locality maps was ready, implying the small area information needed was available for only a limited number of localities. However, the map updating was coordinated with the sample designing in such a way that once the first stage sample of localities was selected, mapping of these localities was given highest priority, thus offering an opportunity to subdivide sample localities into cells with a known measure of (population) size.

The present design is based on listings of localities provided by Barghouti and Daibas (1993) for the West Bank, and Abdeen and Abu-Libdeh (1993) for the Gaza Strip. Even though the population figures are rough estimates as per 1992-93, produced mainly by questioning local administration informants (e.g. Mukhtars) about the number of families in the locality, or projected estimates, they appear to be fairly well attuned with other sources (e.g. Benvenisti and Khayat 1988). Furthermore, the listings applied as a frame comprise more localities than previous ones, and should thus be more complete. However, the coverage may still be less than - although close to - 100% in terms of areas.

The first stage comprises the assigning of localities (as listed by Barghouti and Daibas 1993; Abdeen and Abu Libdeh 1993) to be the Primary Sampling Units (PSUs), the stratification of the PSUs, and the selection of sample PSUs from each stratum. The stratification is a subdivision of the PSUs according to district, administrative status of the locality, and estimated population (households) size. The PSUs were selected independently for each stratum, and with probability proportionate to estimated population size. In the Gaza Strip all localities were selected. The same applies to the district capitals, municipal localities and refugee camps in the West Bank, except in two strata in A Ramallah district. Whenever all PSUs in a stratum are selected, the design is a two stage one, and each single PSU is to be regarded as a separate substratum. The two stage design also applies for several of the small villages (single cell localities). As a matter of fact, the major parts of the sample is selected in two stages only, contributing favorably to smaller sampling error as compared to a strict three stage design.

The second stage subdivision of sample PSUs into cells (or Secondary Sampling Units - SSUs) was done on maps indicating location of buildings and a rough estimate of the number of dwelling in each building. Thus, for each sample PSU or locality as a whole, there are two size measures available; the estimated number of households, and the roughly estimated number of dwelling units. Although these sets of measures proved to be positively correlated, they departed significantly in most cases. However, for the cells, the number of dwelling units were the only measure of size available. Therefore, when selecting the sample cells from each sample PSU with probability proportionate to size, the size in terms of dwelling units had to be applied, i.e. a conceptually different size measure than the one applied at the first stage of selection (households).

For each sample cell the population has been listed by enumeration of buildings (map reference), and dwelling units. It should be noted that the number of dwelling units in each building was assessed by listers from outside no thorough inquiries were made as to whether they were inhabited or not. It was thus expected that errors would occur rather frequently - a problem which is to be evaluated separately on the basis of data collected during the survey. The listing of dwelling units constitutes the Sampling Frame from which the household sample was selected at a third stage by systematic sampling.

The planned sample size was 15,000 households. However, due to the sampling frame imperfections which were envisaged (several non-eligible units included), oversampling was carried out at a rate of approximately 30%, i.e. the gross sample selected at the outset comprised around 20,000 dwelling units.

The sampling design and sample allocation yield a household sample with varying inclusion probabilities. In order to have unbiased results, it is thus recommended that all estimates are based on weighed observations, the weights being the inverse of the respective inclusion probabilities.

All households in a cell have the same probability of being selected, however varying from cell to cell. It should be noted that non-eligible dwelling units (i.e. units which are not inhabited by households) have been removed from the sample. This does not affect the inclusion probabilities or the weights . The actual values of the weights are in the range 0.3 to 3.0. However, 80 % of the weights are in the range 0.7 to 1.4. Only a very few (small) cells are near the extremes.

Since the sampling design is a complex multi-stage one, variance must be calculated with other methods than those applicable to simple random sampling. In order to carry out the calculations, the software CENVAR (US Bureau of the Census 1993) has been used.

Mode of data collection

Face-to-face [f2f]

Research instrument

e Demographic Survey questionnaire consists of seven main parts Control Sheet which includes items related to quality control sample identification interview schedule and interview results Household Roster which includes questions related to the demographic and socio-economic characteristics of persons Household Mortality Schedule which includes questions related to deaths in the household during the past 24 months. Housing Schedule which includes questions on housing and housing conditions Relatives Abroad Schedule which includes questions on the number and the demographic characteristics of close relatives residing abroad Women's Schedule which includes questions mainly related to ever married women age 14-54 years Birth History which includes questions related to the characteristics of all births occurring to ever married women eligible for interview Answers to the first five parts of the questionnaires were obtained by interviewing the household head or any adult member of the household in cases where the head was not present during enumeration The last two sections of the questionnaire were completed by interviewing all eligible women The questionnaire was worded in colloquial Arabic Questions were written in full on the questionnaire and strict instructions were given to interviewers to read all questions verbatim during the interviews

Cleaning operations

A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks logical check range checks consisting checks and cross-validation Weekly thorough checks on the overall consistency of the data files and sample allocation were also performed after data entry Questionnaire containing field-related errors were sent back to the field for corrections EPI-INFO Version 6.02 supported with NAFITHA-Version 4.00 (Arabization program) was used

Abstract

The primary objective of the 2014 LDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health issues such as smoking, knowledge of breast cancer, and male circumcision. In addition, the 2014 LDHS provides estimates of anaemia prevalence among children age 6-59 months and adults, and gives estimates of hypertension, HIV prevalence and HIV incidence among adults. The 2014 LDHS is a follow-up to the 2004 and 2009 LDHS surveys.

The information collected through the LDHS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

Target population for 2014 Lesotho DHS was women (age 15-49) and men (age 15-59) of reproductive age and their young children living in households.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sampling frame used for the 2014 LDHS is an updated frame from the 2006 Lesotho Population and Housing Census (PHC) provided by the Lesotho Bureau of Statistics (BOS). The sampling frame excluded nomadic and institutional populations such as persons in hotels, barracks, and prisons.

The 2014 LDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as in urban and rural areas, four ecological zones, and each of Lesotho's 10 districts. The first stage involved selecting sample points (clusters) consisting of enumeration areas (EAs) delineated for the 2006 PHC. A total of 400 clusters were selected, 118 in urban areas and 282 in rural areas.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected EAs in July 2014, and households to be included in the survey were randomly selected from these lists. About 25 households were selected from each sample point, for a total sample size of 9,942 households. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2014 LDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Lesotho. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Sesotho.

Cleaning operations

In this survey, instead of using paper questionnaires, interviewers used personal digital assistants (PDAs) to record responses during interviews, and team supervisors managed the data using tablet computers. The PDAs and tablets were equipped with Bluetooth technology to enable remote electronic transfer of files (e.g., transfer of assignment sheets from team supervisors to interviewers and transfer of completed questionnaires from interviewers to supervisors). The computer-assisted personal interviewing (CAPI) data collection system employed in the 2014 LDHS was developed by The DHS Program using the mobile version of CSPro.

The data processing operation included secondary editing, which involved resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by one person who took part in the main fieldwork training. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in October 2014 and completed in February 2015.

Response rate

A total of 9,942 households were selected for the sample, of which 9,543 were occupied. Of the occupied households, 9,402 were successfully interviewed, yielding a response rate of 99%. This compares favourably to the 2009 LDHS response rate (98%).

In the interviewed households, 6,818 eligible women were identified for individual interviews; interviews were completed with 6,621 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,133 eligible men were identified and 2,931 were successfully interviewed, yielding a response rate of 94%. The lower response rate for men was likely due to their more frequent and longer absences from the household.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2014 Lesotho Demographic and Health Survey (2014 LDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2014 LDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2014 LDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF International. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

The Taylor linearisation method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.

Note: A more detailed description of estimate of sampling error is presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Sibship size and sex ratio of siblings

Note: See detailed data quality tables in APPENDIX D of the report.

Abstract

The Cambodia Demographic and Health Survey in 2010 (CDHS 2010) is the third nationally representative survey conducted in Cambodia on population and health issues. It uses the same methodology as its predecessors, the 2000 and the 2005 Cambodia Demographic and Health Surveys, allowing policymakers to use these surveys to assess trends over time. The primary objective of the CDHS is to provide the Ministry of Health (MOH), Ministry of Planning (MOP), and other relevant institutions and users with updated and reliable data on infant and child mortality, fertility preferences, family planning behavior, maternal mortality, utilization of maternal and child health services, health expenditures, women’s status, and knowledge and behavior regarding HIV/AIDS and other sexually transmitted infections. This information contributes to policy decisions, planning, monitoring, and program evaluation for the development of Cambodia at both the national and local government levels.

Geographic coverage

The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for 19 domains: 1.Banteay Mean Chey, 2.Kampong Cham, 3.Kampong Chhnang, 4.Kampong Speu, 5.Kampong Thom, 6.Kandal, 7.Phnom Penh, 8.Prey Veng, 9.Pursat, 10.Svay Rieng, 11.Takeo, 12.Kratie, 13.Siem Reap, 14.Otdar Mean Chey, 15. Battambang and Krong Pailin, 16. Kampot and Krong Kep, 17.Krong Preah Sihanouk and Kaoh Kong, 18.Preah Vihear and Steng Treng; and 19.Mondol Kiri and Rattanak Kiri.

Analysis unit

Household, individual (including women and men between the ages of 15 and 49), and children aged 5 and below.

Universe

The survey covered the whole resident population (regular household) , with the exception of homeless in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey was based on a stratified sample selected in two stages. Stratification was achieved by separating every reporting domain into urban and rural areas. Thus, the 19 domains. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratifications were achieved at each of the lower geographical or administrative levels by sorting the sampling frame according to geographical/administrative order and by using a probability proportional to size selection strategy at the first stage of selection. (Please refer to technical doccuments for details).

Mode of data collection

Face-to-face [f2f]

Research instrument

There are three types of questionnaires used in the CDHS: the Household Questionnaire, the Individual Woman's Questionnaire, and the Individual Man's Questionnaire.

The households that have been scientifically selected to be included in the CDHS sample were visited and interviewed using a Household Questionnaire. The Household Questionnaire consisted of a cover sheet to identify the household and a form on which all members of the household and visitors were listed. Data collected about each household member were name, sex, age, education, and survival of parents for children under age 18 years, etc. The Household Questionnaire was used to collect information on housing characteristics such as type of water, sanitation facilities, quality of flooring, and ownership of durable goods.

The Household Questionnaire permitted the interviewer to identify women and men who were eligible for the Individual Questionnaire. Women ages 15-49 years in every selected household who are members of the household (those that usually live in the household) and visitors (those who do not usually live in the household but who slept there the previous night) were eligible to be interviewed with the individual Woman's Questionnaire.

After all of the eligible women in a household have been identified, female interviewers used the Woman's Questionnaire to interview the women. The Woman's Questionnaire collected information on the following topics:

 · socio-demographic characteristics

 · reproduction

 · birth spacing

 · maternal health care and breastfeeding

 · immunization and health of children

 · cause of death of children

 · marriage and sexual activity

 · fertility preferences

 · characteristics of the husband and employment activity of the woman

 · HIV

 · maternal mortality

 · women's status

 · household relations

In one-half of the households, men were identified as eligible for individual interview, and the male interviewer of each team used the Man's Questionnaire to interview the eligible men. Team leaders informed their teams which households in the sample have been selected for including interviews with men. The Man's Questionnaire collected information on the following topics:

 · socio-demographic characteristics

 · reproduction

 · birth spacing

 · marriage and sexual activity

 · HIV

Biomarker data collection were conducted in the same one-half of the households which were selected to include men for interview. The biomarker data collection included: measuring the height and weight of women and children (under age 6 years), anemia testing of women and children, and drawing blood samples from women and men for laboratory testing of HIV. Biomarker data collection were recorded in the Household Questionnaire.

Cleaning operations

Data editing was done in the following data processing stages:

a. Office editing and coding - minimal since CSPro has been designed to be an intelligent data entry program

b. Data entry

c. Completeness of data file

d. Verification of Data - prior to this stage, data are again entered and tagged as V to indicate that the dataset is a verification data

e. Secondary editing

Response rate

Response rate:

Households: 99 per cent

Women ages 15-49: 98 per cent

Men ages 15-49: 95 per cent

See Table 1. Results of the household and individual interviews in the CDHS 2010 Preliminary Report (Refer to technical documents)

Sampling error estimates

The computer software used to calculate sampling errors for the 2010 CDHS is a Macro SAS procedure. This procedure used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. ISSA also computes ISSA computes the design effect (DEFT) for each estimate.

Sampling errors for the 2010 CDHS are calculated for selected variables considered to be of primary interest for woman’s survey and for man’s surveys, respectively for the country as a whole, for urban and rural areas, and for each of the 19 study domains.

Abstract

The 2019-20 Gambia Demographic and Health Survey (2019-20 GDHS) is a nationwide survey with a nationally representative sample of residential households. The survey was implemented by The Gambia Bureau of Statistics (GBoS) in collaboration with the Ministry of Health (MoH).

The primary objective of the 2019-20 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2019-20 GDHS: ▪ collected data on fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; gender; nutrition; awareness about HIV/AIDS; self-reported sexually transmitted infections (STIs); and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) ▪ obtained information on the availability of, access to, and use of mosquito nets as part of the National Malaria Control Programme ▪ gathered information on other health issues such as injections, tobacco use, hypertension, diabetes, and health insurance ▪ collected data on women’s empowerment, domestic violence, fistula, and female genital mutilation/cutting ▪ tested household salt for the presence of iodine ▪ obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and women age 15-49 ▪ conducted anaemia testing of women age 15-49 and children age 6-59 months ▪ conducted malaria testing of children age 6-59 months

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019-20 GDHS was based on an updated version of the 2013 Gambia Population and Housing Census (2013 GPHC) conducted by GBoS. The census counts were updated in 2015-16 based on district-level projected counts from the 2015-16 Integrated Household Survey (IHS). Administratively, The Gambia is divided into eight Local Government Areas (LGAs). Each LGA is subdivided into districts and each district is subdivided into settlements. A settlement, a group of small settlements, or a part of a large settlement can form an enumeration area (EA). These units allow the country to be easily separated into small geographical area units, each with an urban or rural designation. There are 48 districts, 120 wards, and 4,098 EAs in The Gambia; the EAs have an average size of 68 households.

The sample for the 2019-20 GDHS was a stratified sample selected in two stages. In the first stage, EAs were selected with a probability proportional to their size within each sampling stratum. A total of 281 EAs were selected.

In the second stage, the households were systematically sampled. A household listing operation was undertaken in all of the selected clusters. The resulting lists of households served as the sampling frame from which a fixed number of 25 households were systematically selected per cluster, resulting in a total sample size of 7,025 selected households. Results from this sample are representative at the national, urban, and rural levels and at the LGA levels.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019-20 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to The Gambia. Suggestions were solicited from various stakeholders representing government ministries, departments, and agencies; nongovernmental organisations; and international donors. All questionnaires were written in English, and interviewers translated the questions into the appropriate local language to carry out the interview.

Cleaning operations

All electronic data files were transferred via the Internet File Streaming System (IFSS) to the GBoS central office. The IFSS automatically encrypts the data and sends the data to a server, and the server in turn downloads the data to the data processing supervisor’s password-protected computer in the central office. The data processing operation included secondary editing, which required resolution of computeridentified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and three secondary editors who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in November 2019 and completed in May 2020.

Response rate

All 6,985 households in the selected housing units were eligible for the survey, of which 6,736 were occupied. Of the occupied households, 6,549 were successfully interviewed, yielding a response rate of 97%. Among the households successfully interviewed, 1,948 interviews were completed in 2019 and 4,601 in 2020.

In the interviewed households, 12,481 women age 15-49 were identified for individual interviews; interviews were completed with 11,865 women, yielding a response rate of 95%, a 4 percentage point increase from the 2013 GDHS. Among men, 5,337 were eligible for individual interviews, and 4,636 completed an interview; this yielded a response rate of 87%, a 5 percentage point increase from the previous survey.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019-20 Gambia Demographic and Health Survey (GDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019-20 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019-20 GDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Completeness of reporting
• Births by calendar years
• Reporting of age at death in days
• Reporting of age at death in months
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Number of enumeration areas completed by month, according to Local Government Area, The Gambia DHS 2019-20
• Percentage of children age 6-59 months classified as having malaria according to RDT, by month and Local Government Area, The Gambia DHS 2019-20
• Completeness of information on siblings
• Sibship size and sex ratio of siblings

See details of the data quality tables in Appendix C of the final report.

Abstract

The main purpose of a Household Income and Expenditure Survey (HIES) was to present high quality and representative national household data on income and expenditure in order to update Consumer Price Index (CPI), improve statistics on National Accounts and measure poverty within the country.

The main objectives of this survey - update the weight of each expenditure item (from COICOP) and obtain weights for the revision of the Consumer Price Index (CPI) for Funafuti - provide data on the household sectors contribution to the National Accounts - design the structure of consumption for food secutiry - To provide information on the nature and distribution of household income, expenditure and food consumption patterns household living standard useful for planning purposes - To provide information on economic activity of men and women to study gender issues - To generate the income distribution for poverty analysis

The 2010 Household Income and Expenditure Survey (HIES) is the third HIES that was conducted by the Central Statistics Division since Tuvalu gained political independence in 1978.

This survey deals mostly with expenditure and income on the cash side and non cash side (gift, home production). Moreover, a lot of information are collected:

at a household level: - goods possession - description of the dwelling - water tank capacity - fruits and vegetables in the garden - livestock

at an individual level: - education level - employment - health

Geographic coverage

National Coverage: Funafuti and /Outer islands.

Analysis unit

• Household level
• Individual level

Universe

The scope of the 2010 Household Income and Expenditure Survey (HIES) was all occupied households in Tuvalu. Households are the sampling unit, defined as a group of people (related or not) who pool their money, and cook and eat together. It is not the physical structure (dwelling) in which people live. HIES covered all persons who were considered to be usual residents of private dwellings (must have been living in Tuvalu for a period of 12-months, or have intention to live in Tuvalu for a period of 12-months in order to be included in the survey). Usual residents who are temporary away are included as well (e.g., for work or a holiday).

All the private household are included in the sampling frame. In each household selected, the current resident are surveyed, and people who are usual resident but are currently away (work, health, holydays reasons, or border student for example. If the household had been residing in Tuvalu for less than one year: - but intend to reside more than 12 months => he is included - do not intend to reside more than 12 months => out of scope.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tuvalu 2010 Household Income and Expenditure Survey (HIES) outputs breakdowns at the domain level which is Funafuti and Outer Islands. To achieve this, and to match the budget constraint, a third of the households were selected in both domains. It was decided that 33% (one third) sample was sufficient to achieve suitable levels of accuracy for key estimates in the survey. So the sample selection was spread proportionally across all the islands except Niulakita as it was considered too small. The selection method used is the simple random survey, meaning that within each domain households were directly selected from the population frame (which was the updated 2009 household listing). All islands were included in the selection except Niulakita that was excluded due to its remoteness, and size.

For selection purposes, in the outer island domain, each island was treated as a separate strata and independent samples were selected from each (one third). The strategy used was to list each dwelling on the island by their geographical position and run a systematic skip through the list to achieve the 33% sample. This approach assured that the sample would be spread out across each island as much as possible and thus more representative.

Population and sample counts of dwellings by islands for 2010 HIES Islands: -Nanumea: Population: 123; sample: 41 -Nanumaga: Population: 117; sample: 39 -Niutao: Population: 138; sample: 46 -Nui: Population: 141; sample: 47 -Vaitupu: Population: 298; sample: 100 -Nukufetau: Population: 141; sample: 47 -Nukulaelae: Population: 78; sample: 26 -Funafuti: Population: 791; sample: 254 -TOTAL: Population: 1827; sample: 600.

Mode of data collection

Face-to-face [f2f]

Research instrument

3 forms were used. Each question is writen in English and translated in Tuvaluan on the same version of the questionnaire. The questionnaire was highly based on the previous one (2004 survey).

Household Schedule This questionnaire, to be completed by interviewers, is used to collect information about the household composition, living conditions and is also the main form for collecting expenditure on goods and services purchased infrequently.

• composition of the household and demographic profile of each members
• dwelling information
• dwelling expenditure
• transport expenditure
• education expenditure
• health expenditure
• land and property expenditure
• household furnishing
• home appliances
• cultural and social payments
• holydays/travel costs
• Loans and saving
• clothing
• other major expenditure items

Individual Schedule There will be two individual schedules: - health and education - labor force (individual aged 15 and above) - employment activity and income (individual aged 15 and above): wages and salaries working own business agriculture and livestock fishing income from handicraft income from gambling small scale activies jobs in the last 12 months other income childreen income tobacco and alcohol use other activities seafarer

Diary (one diary per week, on a 2 weeks period, 2 diaries per household were required) The diaries are used to record all household expenditure and consumption over the two week diary keeping period. The diaries are to be filled in by the household members, with the assistance from interviewers when necessary. - All kind of expenses - Home production - food and drink (eaten by the household, given away, sold) - Goods taken from own business (consumed, given away) - Monetary gift (given away, received, winning from gambling) - Non monetary gift (given away, received, winning from gambling).

Cleaning operations

Consistency of the data: - each questionnaire was checked by the supervisor during and after the collection - before data entry, all the questionnaire were coded - the CSPRo data entry system included inconsistency checks which allow the National Statistics Office staff to point some errors and to correct them with imputation estimation from their own knowledge (no time for double entry), 4 data entry operators. 1. presence of all the form for each household 2. consistency of data within the questionnaire

at this stage, all the errors were corrected on the questionnaire and on the data entry system in the meantime.

• after data entry, the extreme amount of each questionnaire where selected in order to check their consistency. at this stage, all the inconsistency were corrected by imputation on CSPRO editing.

Response rate

The final response rates for the survey was very pleasing with an average rate of 97 per cent across all islands selected. The response rates were derived by dividing the number of fully responding households by the number of selected households in scope of the survey which weren't vacant.

Response rates for Tuvalu 2010 Household Income and Expenditure Survey (HIES): - Nanumea 100% - Nanumaga 100% - Niutao 98% - Nui 100% - Vaitupu 99% - Nukufetau 89% - Nukulaelae 100% - Funafuti 96%

As can be seen in the table, four of the islands managed a 100 per cent response, whereas only Nukufetau had a response rate of less than 90 per cent.

Further explanation of response rates can be located in the external resource entitled Tuvalu 2010 HIES Report Table 1.2.

Sampling error estimates

The quality of the results can be found in the report provided in this documentation.

Abstract

The Ghana Demographic and Health Survey (GDHS) is a national sample survey designed to provide information on fertility, family planning and health in Ghana. The survey, which was conducted by the Statistical Service of Ghana, is part of a worldwide programme coordinated by the Institute for Resource Development/Macro Systems, Inc., in more than 40 countries in Africa, Asia and Latin America.

The short-term objectives of the Ghana Demographic and Health Survey (GDHS) are to provide policymakers and those implementing policy with current data on fertility levels, knowledge and use of contraception, reproductive intentions of women 15-49, and health indicators. The information will also serve as the basis for monitoring and evaluating programmes initiated by the government such as the extended programme on immunization, child nutrition, and the family planning programme. The long-term objectives are to enhance the country's ability to undertake surveys of excellent technical quality that seek to measure changes in fertility levels, health status (particularly of children), and the extent of contraceptive knowledge and use. Finally, the results of the survey will form part of an international data base for researchers investigating topics related to the above issues.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

The 150 clusters from which a representative sample of women aged 15-49 was selected from a subsample of the 200 clusters used for the Ghana Living Standards Survey (GLSS). All census Enumeration Areas (EAs) were first stratified by ecological zones into 3 strata, namely Coastal Savanna, Forest, and Northern Savanna. These were further stratified into urban, semi-urban, and rural EAs. The EAs (in some cases, segments of EAs) were then selected with probability proportional to the number of households. All households in the selected EAs were subsequently listed.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face

Research instrument

Three different types of questionnaires were used for the GDHS. These were the household, individual and the husband questionnaires. The household and the individual questionnaires were adapted from the Model "B" Questionnaire for the DHS program. The GDHS is one of the few surveys in which special effort was made to collect information from husbands of interviewed women on such topics as fertility preferences, knowledge and use of contraception, and environmental and health related issues.

All usual members and visitors in the selected households were listed on the household questionnaire. Recorded in the household questionnaire were data on the age and sex of all listed persons in addition to information on fostering for children aged 0-14. Eligible women and eligible husbands were also identified in the household questionnaire.

The individual questionnaire was used to collect data on eligible women. Eligible women were definedas those aged 15-49 years who spent the night prior to the household interview in the selected household, irrespective of whether they were usual members of the household or not. Items of information collected in this questionnaire are as follows: 1) Respondent's Background 2) Reproductive Behavior 3) Knowledge and Use of Contraception 4) Health and Breastfeeding 5) Marriage 6) Fertility Preferences 7) Husband's Background and Women's Work 8) Weight and Height of Children Aged 3-36 Months.

In half of the selected clusters a husband's questionnaire was used to collect data on eligible husbands. Eligible husbands were defined as those who were co-resident with their wives and whose wives had been successfully interviewed. Data on the husband's background, contraceptive knowledge and use, as well as fertility preferences were collected.

All three questionnaires were translated into seven local languages, namely, Twi, Fante, Nzema, Ga, Ewe, Hausa and Dagbani. All the GDHS interviewers were able to conduct interviews in English and at least one local language. The questionnaires were pretested from mid-October to early November 1987. Five teams were used for the pretest fieldwork. These included 19 persons who were trained for 11 days.

Cleaning operations

Completed questionnaires were collected weekly from the regions by the field coordinators. Coding, data entry and machine editing went on concurrently at the Ghana Statistical Service in Accra as the fieldwork progressed. Coding and data entry were started in March 1988 and were completed by the end of June 1988. Preliminary tabulations were produced by mid-July 1988, and by August 1988 preliminary results of the survey were published.

Response rate

Of the 4966 households selected, 4406 were successfully interviewed. Excluding 9 percent of households that were vacant, absent, etc., the household response rate is 98 percent.

Out of 4574 eligible women in the household schedule, 4488 were interviewed successfully. The response rate at the individual level is 98 percent. Of the 997 eligible husbands, 943 were successfully interviewed, representing a response rate of 95 percent.

Sampling error estimates

The results from sample surveys are affected by two types of errors: non-sampling error and sampling error. The former is due to mistakes in implementing the field activities, such as failing to locate and interview the correct household, errors in asking questions, data entry errors, etc. While numerous steps were taken to minimize this sort of error in the GDHS, non-sampling errors are impossible to avoid entirely, and are difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of women selected in the GDHS is only one of many samples of the same size that could have been drawn from the population using the same design. Each sample would have yielded slightly different results from the sample actually selected. The variability observed among all possible samples constitutes sampling error, which can be estimated from survey results (though not measured exactly).

Sampling error is usually measured in terms of the "standard error" (SE) of a particular statistic (mean, percentage, etc.), which is the square root of the variance of the statistic across all possible samples of equal size and design. The standard error can be used to calculate confidence intervals within which one can be reasonably sure the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples of identical size and design will fall within a range of plus or minus two times the standard error of that statistic.

If simple random sampling had been used to select women for the GDHS, it would have been possible to use straightforward formulas for calculating sampling errors. However, the GDHS sample design used three stages and clusters of households, and it was necessary to use more complex formulas. Therefore, the computer package CLUSTERS, developed for the World Fertility Survey, and was used to compute sampling errors.

Note: See detailed estimate of sampling error calculation in APPENDIX C of the survey report.

Release Date: 2023-05-11.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY23-0262)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown by the following legal form of organization (LFO) categories:. S-Corporations. C-Corporations. Individual proprietorships. Partnerships...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. For C-corporations, there is no tax form or business registry that clearly and unequivocally identifies all owners of this type of business. For this reason, the Census Bureau is unable to assign demographic characteristics for C-corporations. Data for C-corporations are included in the published tables but are not shown by the demographic characteristics of the firms....Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). Rail Transportation (NAICS 482). Postal Service (NAICS 491). Monetary Authorities-Central Bank (NAICS 521). Funds, Trusts, and Other Financial Vehicles (NAICS 525). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2019/AB1900NESD03.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2019/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the level of noise applied to the data:. G - Low noise: The cell valu...

File List Supplement1.xls (md5: 4202b5bccb5ee828f646f50530394c47)

  Please be advised that the ESA cannot guarantee the forward migration of proprietary file formats such as Excel (.xls) documents.
Description
  SupplementA.xls is an Excel spreadsheet containing 5 sheets with example calculations. The first 4 sheets (labeled Model 1 - Model 4) contain calculations for models considered in APPLICATION TO YELLOWSTONE BISON:
  Model 1: Makes no assumptions about equality of survival rates for different age classes.
  Model 2: Assumes survival rates are equal for ages 0–1, 2–3, 4–5, 6–7, 8–9, 10–11, 12–13.
  Model 3: Assumes survival rates are equal for ages 0–1, 2–3, 4–5, 6–11, 12–13.
  Model 4: Assumes survival rates are equal for ages 0–13.
  The last sheet (labeled 3 Years) contains calculations for a hypothetical example with 3 age classes and 3 years of data, and no assumptions about equality of survival rates.

Abstract

The 2003 Turkey Demographic and Health Survey (TDHS-2003) is a nationally representative sample survey designed to provide information on levels and trends on fertility, infant and child mortality, family planning and maternal and child health. Survey results are presented at the national level, by urban and rural residence, and for each of the five regions in the country. The TDHS2003 sample also allows analyses for some of the survey topics for the 12 geographical regions (NUTS1) which were adopted at the second half of 2002 within the context of Turkey's move to join the European Union.

Funding for the TDHS-2003 was provided initially by the Government of Turkey, as a project in the annual investment program of the State Planning Organization, and further funding was obtained from the European Union through the Turkey Reproductive Health Program implemented by the Ministry of Health.

The survey was fielded between December 2003 and May 2004. Interviews were completed with 10,836 households and with 8,075 ever-married women at reproductive ages (15-49). Ever-married women at ages 15-49 who were present in the household on the night before the interview or who usually live in that household were eligible for the survey.

The 2003 Turkish Demographic and Health Survey (TDHS-2003) is the latest in a series of national-level population and health surveys that have been conducted by the Hacettepe University Institute of Population Studies (HUIPS), in the last four decades. The primary objective of the TDHS-2003 is to provide data on socioeconomic characteristics of households and women, fertility, mortality, marriage patterns, family planning, maternal and child health, nutritional status of women and children, and reproductive health. The survey obtained detailed information on these issues from a sample of ever-married women in the reproductive ages (15-49). The TDHS-2003 was designed to produce information in the field of demography and health that to a large extent can not be obtained from other sources.

Specifically, the objectives of the TDHS-2003 included: - Collecting data at the national level that allows the calculation of demographic rates, particularly fertility and childhood mortality rates; - Obtaining information on direct and indirect factors that determine levels and trends in fertility and childhood mortality; - Measuring the level of contraceptive knowledge and practice by method, region, and urban-rural residence; - Collecting data relative to mother and child health, including immunizations, prevalence and treatment of acute respiratory tract infections among children under five, antenatal care, assistance at delivery, and breastfeeding; - Measuring the nutritional status of children under five and of their mothers; and - Collecting data at the national level on elderly welfare, knowledge of sexually transmitted diseases (STDs) and AIDS, and usage of iodide salt.

The TDHS-2003 information is intended to contribute data to assist policy makers and administrators to evaluate existing programs and to design new strategies for improving demographic, social and health policies in Turkey. Another important purpose of the TDHS2003 is to sustain the flow of information for the interested organizations in Turkey and abroad on the Turkish population structure in the absence of reliable and sufficient vital registration system.

SUMMARY OF FINDINGS

The results show that there have been important changes in various demographic and health indicators in a more positive direction than expected. The fertility data indicate that Turkey is achieving “replacement” fertility. The survey findings also document improvements in infant and child mortality and progress in mother and child health services.

Geographic coverage

The sample was designed to provide estimates for: - Turkey as a whole; - Urban and rural areas (each as a separate domain); - Each of the conventional major five regions of the country, namely the West, South, Central, North, and East regions - The 12 NUTS 13 regions, for selected indicators which are based on sufficient number of observations

Analysis unit

• Household
• Women age 15-49
• Children under five

Universe

The population covered by the 1998 DHS is defined as the universe of all ever-married women age 15-49 in the household who were identified as eligible in the household schedule were interviewed. In addition, some information was collected for households and women in a sub-sample of one-half of all households.

Kind of data

Sample survey data

Sampling procedure

A weighted, multistage, stratified cluster sampling approach was used in the selection of the TDHS-2003 sample. The sample was designed in this fashion because of the need to provide estimates for a variety of characteristics for various domains. These domains, which are frequently employed in the tabulation of major indicators from the survey, are: - Turkey as a whole; - Urban and rural areas (each as a separate domain); - Each of the conventional major five regions of the country, namely the West, South, Central, North, and East regions - The 12 NUTS 13 regions, for selected indicators which are based on sufficient number of observations

The major objective of the TDHS-2003 sample design was to ensure that the survey would provide estimates with acceptable precision for these domains for most of the important demographic characteristics, such as fertility, infant and child mortality, and contraceptive prevalence, as well as for the health indicators.

SAMPLE FRAME

Different criteria have been used to describe "urban" and "rural" settlements in Turkey. In the demographic surveys of the 1970s, a population size of 2,000 was used to differentiate between urban and rural settlements. In the 1980s, the cut-off point was increased to 10,000 and, in some surveys in the 1990s, to 20,000. A number of surveys used information on the administrative status of settlements in combination with population size for the purpose of differentiation. The urban frame of the TDHS-2003 consisted of a list of provincial centers, district centers, and other settlements with populations larger than 10,000, regardless of administrative status. The rural frame consisted of all district centers, sub-districts and villages not included in the urban frame. The urban-rural definitions of the TDHS-2003 are identical with those in the TDHS-1998.

Initial information on all settlements in Turkey was obtained from the 2000 General Population Census. The results of 2000 General Population Census provided a computerized list of all settlements (provincial and district centers, sub-districts and villages), their populations and the numbers of households.

STRATIFICATION

Currently Turkey is divided administratively into 81 provinces. For purposes of selection in prior surveys in Turkey, these provinces have been grouped into five regions. This regional breakdown has been popularized as a powerful variable for understanding the demographic, social, cultural, and economic differences between different parts of the country. The five regions, West, South, Central, North, and East regions, include varying numbers of provinces.

In addition to the conventional five geographic regions, a new system of regional breakdown was adopted in late 2002. In accordance with the accession process of Turkey to the European Union, the State Planning Office and the State Institute of Statistics constructed three levels of NUTS regions, which have since become official (Law No. 2002/4720). "NUTS" stands for "The Nomenclature of Territorial Units for Statistics". NUTS is a statistical region classification that is used by member countries of European Union (EU). The 81 provinces were designated as regions of NUTS 3 level; these were further aggregated into 26 regions to form the NUTS 2 regions. NUTS 1 regions were formed by aggregating NUTS 2 regions into 12 regions. Two of the NUTS 1 regions, Istanbul and the Southeastern Anatolia, were given special attention in the sample design process and a comparatively larger share of the total sample was allocated to these regions to ensure that statistically sound estimates for a larger number of indicators would be obtained than would be the case for the remaining 10 NUTS 1 regions. Policymakers, researchers and other concerned circles had voiced interest in information on demographic and health indicators for Istanbul and the Southeastern Anatolian regions in the past. Furthermore, as an add-on study, the Istanbul metropolitan area was designated by UN-Habitat as one of the mega-cities in their International Slum Survey series. In co-operation with UN-Habitat, HUIPS wished to be able to produce estimates for slum4 and non-slum areas within Istanbul; for this reason, the total sample size for Istanbul was kept at a relatively high magnitude.

One of the priorities of the TDHS-2003 was to produce a sample design that was methodologically and conceptually consistent with the designs of previous demographic surveys carried out by the Hacettepe Institute of Population Studies. In surveys prior to the TDHS-1993, the five-region breakdown of the country was used for stratification. In TDHS-1993, a more detailed stratification taking into account subregions was employed to obtain a better dispersion of the sample. The criteria for subdividing the five major regions into subregions were the infant mortality rates of each province, estimated from the 1990 Population Census using indirect techniques.5 Using the infant mortality estimates as well as geographic proximity, the provinces in each region were grouped into 14 subregions at the time of the TDHS-1993. The sub-regional division

Abstract

A National Census of Population and Housing could not be ventured due to the disturbances in the Northern and eastern Provinces. Hence the Dept of Census and Statistics has decided to conduct an island-wide large scale demographic survey (excluding the Northern and Eastern Provinces) during the year 1994 to satisfy the urgent needs of the data users, with a view to furnish estimates at Divisional Secretariat, District, Provincial and National levels.

Geographic coverage

National coverage (excluding Northern and Eastern Provinces)

Analysis unit

Housing Unit

A housing unit has been defined as a place of residence:

1. which is separate from other places of residence, ie where there are walls or partitions separating it so that the persons occupying it can live separately from other persons in the building or in the locality and 2. which has independent access.

Living Quarters other than housing units

Building or a group of buildings where a number of persons (generally not related to one another) reside under the supervision of a central authority, eg convents, school, hostels, police barracks, boarding houses etc

Non Housing unit

Every building or part of a building which is not a place of residence and does not form part of a housing unit is regarded as a non-housing unit.

Household

A household may be (a) a one person Household or (b) a multi-person household

A one person household is one where a person lives by himself and makes separate provision for his food (either cooking it himself or purchasing it)

A multi person household is a group of two or more persons live together and have a common arrangement for cooking and partaking of food (in short, living and eating together). The household includes not only members of the family but also others who live with the family and share meals with them such as relatives boarders servants. The members of a household could be unrelated.

In the case of lodgers living with a household and having their own arrangements for meals, each lodger should be treated as a separate household. But boarders who share meals with the household should be treated as members of the household.

a housing unit may consist of one or more households.

Universe

The population living in housing units alone were selected for the survey. Institutional population such as those who are living in barracks, hostels etc has not been encompassed. Accordingly, the estimates reflect a coverage confined to the institutional population who were accounted for 2.3% of the entire population in Sri Lanka in 1981 which could be considerably higher at present. Nontheless the household definition has been modified to incorporate all the households without an upper limit for boarders and lodgers. Therefore the data user should note this distinction of population when comparing with other data.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 92,180 housing units distributed in the island barring Northern and Eastern Provinces was picked for this survey. Stratification was done at sectoral level and all the Divisional Secretary areas were taken as domains. A minimal samples of 300 housing units were selected from each DSD in order to give estimates at these levels. Percentage of Urban housing units in the country was 13% and the balance 87% represented the Rural housing units. When allocating the total sample into these two sectors however Urban (MC UC sector) was over sampled because this sector is more heterogeneous in terms of the characteristics, which were to be collected through this survey. As such at national level 21360 housing units (23%) were allocated to Urban sector and 70820 housing units (77%) were allocated to Rural sector.

A stratified two stage sample design was used with GN Division or part of the GN Division as primary sampling unit (PSU) and housing unit as the secondary sampling unit (SSU) in the rural sector. Rural sector covers about 219 DS Divisions. 3541 PSU's were selected from this sector and 20 housing units selected from each selected PSU.

Urban sector covered all the Municipal Councils and urban Councils in the island (excl North and east). A stratified three stage sample design was adopted with PPS selection of Wards and subsequent selection of a part of Ward as PSU and the housing unit as the final sampling unit were done. About 40% of the wards in each MC/UC was selected as PPS with replacement. Thereafter SSU's were selected from each selected ward. Finally 40 housing unit's were selected from each selected PSU. The Urban Sector represents 10 MCs and 32 UC's in 42 Divisional Secretariat Divisions.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is similar to which is usually administered in the Census of Population and Housing with few exceptions. Housing questions were filled only in the schedule of the main household of the housing unit. The information as collected in the Housing Section (H1-H.13) has been processed in order to tabulate the housing data.

Cleaning operations

Standard Data editing process of DPD/DCS

Response rate

Estimates given in the publication - Demographic Survey 1994 Sri Lanka - Feb 1996 - are subject to standard sampling errors due to enumeration of only selected housing units representing the population. An account of non sampling error is also not readily available for reference.

an adjustment for non-response and coverage errors have been done while inflating the data.