Abstract

The 1998 Ghana Demographic and Health Survey (GDHS) is the latest in a series of national-level population and health surveys conducted in Ghana and it is part of the worldwide MEASURE DHS+ Project, designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 1998 GDHS is to provide current and reliable data on fertility and family planning behaviour, child mortality, children’s nutritional status, and the utilisation of maternal and child health services in Ghana. Additional data on knowledge of HIV/AIDS are also provided. This information is essential for informed policy decisions, planning and monitoring and evaluation of programmes at both the national and local government levels.

The long-term objectives of the survey include strengthening the technical capacity of the Ghana Statistical Service (GSS) to plan, conduct, process, and analyse the results of complex national sample surveys. Moreover, the 1998 GDHS provides comparable data for long-term trend analyses within Ghana, since it is the third in a series of demographic and health surveys implemented by the same organisation, using similar data collection procedures. The GDHS also contributes to the ever-growing international database on demographic and health-related variables.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The major focus of the 1998 GDHS was to provide updated estimates of important population and health indicators including fertility and mortality rates for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of key variables for the ten regions in the country.

The list of Enumeration Areas (EAs) with population and household information from the 1984 Population Census was used as the sampling frame for the survey. The 1998 GDHS is based on a two-stage stratified nationally representative sample of households. At the first stage of sampling, 400 EAs were selected using systematic sampling with probability proportional to size (PPS-Method). The selected EAs comprised 138 in the urban areas and 262 in the rural areas. A complete household listing operation was then carried out in all the selected EAs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, a systematic sample of 15 households per EA was selected in all regions, except in the Northern, Upper West and Upper East Regions. In order to obtain adequate numbers of households to provide reliable estimates of key demographic and health variables in these three regions, the number of households in each selected EA in the Northern, Upper West and Upper East regions was increased to 20. The sample was weighted to adjust for over sampling in the three northern regions (Northern, Upper East and Upper West), in relation to the other regions. Sample weights were used to compensate for the unequal probability of selection between geographically defined strata.

The survey was designed to obtain completed interviews of 4,500 women age 15-49. In addition, all males age 15-59 in every third selected household were interviewed, to obtain a target of 1,500 men. In order to take cognisance of non-response, a total of 6,375 households nation-wide were selected.

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

Mode of data collection

Face-to-face

Research instrument

Three types of questionnaires were used in the GDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were based on model survey instruments developed for the international MEASURE DHS+ programme and were designed to provide information needed by health and family planning programme managers and policy makers. The questionnaires were adapted to the situation in Ghana and a number of questions pertaining to on-going health and family planning programmes were added. These questionnaires were developed in English and translated into five major local languages (Akan, Ga, Ewe, Hausa, and Dagbani).

The Household Questionnaire was used to enumerate all usual members and visitors in a selected household and to collect information on the socio-economic status of the household. The first part of the Household Questionnaire collected information on the relationship to the household head, residence, sex, age, marital status, and education of each usual resident or visitor. This information was used to identify women and men who were eligible for the individual interview. For this purpose, all women age 15-49, and all men age 15-59 in every third household, whether usual residents of a selected household or visitors who slept in a selected household the night before the interview, were deemed eligible and interviewed. The Household Questionnaire also provides basic demographic data for Ghanaian households. The second part of the Household Questionnaire contained questions on the dwelling unit, such as the number of rooms, the flooring material, the source of water and the type of toilet facilities, and on the ownership of a variety of consumer goods.

The Women’s Questionnaire was used to collect information on the following topics: respondent’s background characteristics, reproductive history, contraceptive knowledge and use, antenatal, delivery and postnatal care, infant feeding practices, child immunisation and health, marriage, fertility preferences and attitudes about family planning, husband’s background characteristics, women’s work, knowledge of HIV/AIDS and STDs, as well as anthropometric measurements of children and mothers.

The Men’s Questionnaire collected information on respondent’s background characteristics, reproduction, contraceptive knowledge and use, marriage, fertility preferences and attitudes about family planning, as well as knowledge of HIV/AIDS and STDs.

Response rate

A total of 6,375 households were selected for the GDHS sample. Of these, 6,055 were occupied. Interviews were completed for 6,003 households, which represent 99 percent of the occupied households. A total of 4,970 eligible women from these households and 1,596 eligible men from every third household were identified for the individual interviews. Interviews were successfully completed for 4,843 women or 97 percent and 1,546 men or 97 percent. The principal reason for nonresponse among individual women and men was the failure of interviewers to find them at home despite repeated callbacks.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

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 shortfalls 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 1998 GDHS 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 1998 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 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 1998 GDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1998 GDHS is the ISSA Sampling Error Module. This module uses the Taylor linearization method of 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.

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

Note: See detailed tables in APPENDIX C of the survey report.

Dataset containing variables extracted from original articles published in Peruvian journals.

Abstract

The health and wealth of a nation and its potential to develop and grow depend on its ability to feed its people. To help ensure that food will remain available to those who need it, there is nothing more important to give priority to than agriculture. Accurate and timely statistics about the basic produce and supplies of agriculture are essential to assess the agricultural situation. To help policy maker's deal with the fundamental challenge they are faced within the agricultural sector of the economy and develop measures and policies to maintain food security, there should be a continuous provision of statistics. The collection of reliable, comprehensive and timely data on agriculture is thus required for the above purposes. In this perspective, the Central Statistical Agency (CSA) has endeavored to generate agricultural data for policy makers and other users. The general objective of CSA's annual Agricultural Sample Survey (AgSS) is to collect basic quantitative information on the country's agriculture that is considered essential for development planning, socio-economic policy formulation, food security, etc. The AgSS is composed of four components: Crop production forecast survey, Main (“Meher”) season survey, Livestock survey, and survey of the “Belg” season crop area and production.

The specific objectives of the Main (“Meher”) season area and production survey are: - To estimate the total cultivated land area, production and yield per hectare of major crops (temporary). - To estimate the total farm inputs applied area and quantity of inputs applied by type for major temporary and permanent crops.

Geographic coverage

The survey covered all sedentary rural agricultural population in all regions of the country except urban and nomadic areas which were not included in the survey.

Analysis unit

Agricultural household/ Holder/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2000/2001 (1993 E.C) Meher season agricultural sample survey covered the rural part of the country except three zones in Afar regional state and six zones in Somalie regional state that are predominantly nomadic. A two-stage stratified sample design was used to select the sample. Each zones/special wereda was adopted as stratum for which major findings of the survey are reported except the four regions; namely, Gambella, Harari, Addis Ababa and Dire Dawa which were considered as strata/reporting levels. The primary sampling units (PSUs) were enumeration areas (EAs) and agricultural households were the secondary sampling units. The survey questionnaires were administered to all agricultural holders within the sample households. A fixed number of sample EAs were determined for each stratum/reporting level based on precision of major estimates and cost considerations. Within each stratum EAs were selected using probability proportional to size systematic sampling; size being total number of agricultural households in the EAs as obtained from the 1994 population and housing census. From each sample EA, 40 agricultural households were systematically selected for the annual agricultural sample survey from a fresh list of households prepared at the beginning of the field work of the annual agricultural survey. Of the forty agricultural households, the first twenty-five were used for obtaining information on area under crops, Meher and Beleg season production of crops, land use, agricultural practices, crop damage, and quantity of agricultural households sampled in each of the selected EAs, data on crop cutting were collected for only the fifteen households (11th - 25th households selected). A total of 1,430 EAs were selected for the survey. However, 8 EAs were closed for various reasons beyond the control of the Authority and the survey succeeded in covering 1422 (99.44%) EAs. Within respect to ultimate sampling units, for the Meher season agricultural sample survey, it was planned to cover 35,750 agricultural households.

Note: Distribution of the number of sampling units sampled and covered by strata is given in Appendix I of the 2000-2001 annual Agricultural Sample Survey report which is provided as external resource.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2000-2001 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. Lists of forms in the questionnaires: - AgSS Form 93/0: Used to list all households and agricultural holders in the sample enumeration areas. - AgSS Form 93/1: Used to list selected households and agricultural holders in the sample enumeration areas. - AgSS Form 93/3A: Used to list fields and agricultural practices only pure stand temporary and permanent crops, list of fields and agricultural practices for mixed crops, other land use, quantity of improved and local seeds by type of crop and type and quantity of crop protection chemicals. - AgSS Form 93/4A: Used to collect results of area measurement. - AgSS Form 93/5: Used to list fields for selecting fields for crop cuttings and collect information about details of crop cutting.

Note: The questionnaires are presented in the Appendix IV of the 2000-2001 Agricultural Sample Survey Volume I report which is provided as external resource.

Cleaning operations

Editing, Coding and Verification: In order to insure the quality of the collected survey data an editing, coding and verification instruction manual was prepared and printed. Then 23 editors-coders and 22 verifiers were trained for two days in the editing, coding and verification operation using the aforementioned manual as a reference and teaching aid. The completed questionnaires were edited, coded and later verified on a 100% basis before the questionnaires were passed over to the data entry unit. The editing, coding and verification exercise of all questionnaires was completed in about 30 days.

Data Entry, Cleaning and Tabulation: Before starting data entry, professional staff of Agricultural Statistics Department prepared edit specifications to use on personal computers utilizing the Integrated Microcomputer Processing System (IMPS) software for data consistency checking purposes. The data on the coded questionnaires were then entered into personal computers using IMPS software. The data were then checked and cleaned using the edit specification prepared earlier for this purpose. The data entry operation involved about 31 data encoders and it took 28 days to complete the job. Finally, tabulation was done on personal computers to produce results as indicated in the tabulation plan.

Response rate

A total of 1,430 EAs were selected for the survey. However, 8 EAs were closed for various reasons beyond the control of the Authority and the survey succeeded in covering 1422 (99.44%) EAs. Within respect to ultimate sampling units, for the Meher season agricultural sample survey, it was planned to cover 35,750 agricultural households. The response rate was found to be 99.14%.

Sampling error estimates

Estimation procedures of parameters of interest (total and ratio) and their sampling error is presented in Appendix II of the 2000-2001 annual Agricultural Sample Survey report which is provided as external resource.

The statistical data generated through the administration of the Federal milk order program is recognized widely as one of the benefits of this program. These data provide comprehensive and accurate information on milk supplies, utilization, and sales, as well as class prices established under the orders and prices paid to dairy farmers (producers). The sources of this data are monthly reports of receipts and utilization, producer payroll reports, and reports of nonpool handlers filed by milk processors (handlers) subject to the provisions of the various milk orders. The local market administrator (MA) uses these reports to determine pool obligations under the order and to verify proper payments to producers. Auditors employed by the MA review handler records to assure the accuracy of reported information. Reporting errors are corrected; if necessary, pool obligations are revised.

After the pool obligations have been determined the local market administrator summarizes the individual handler reports and submits a series of order summary reports to the Market Information Branch (MIB) in Dairy Programs. The MIB summarizes the individual order data and disseminates this information via monthly, bimonthly, and annual releases or publications. Since milk marketing order statistics are based on reports filed by the population of possible reporting firms and not a sample, these statistics are comprehensive. Also, since these individual firm reports are subject to audit and verification, these statistics are accurate.

The Federal milk order statistics database contains historical information, beginning in January 2000, generated by the administration of the Federal milk order program. Most of the information in the database has been published previously by the Market Information Branch in Dairy Programs either on its web site or in the Dairy Market News Report. New users are encouraged to use the "User Guide" to learn how to navigate the search screens. If you are interested in a description of the Federal milk order statistics program, or want current data, in ready made table form, use the "Current Information" link.

Abstract

The 1997 Jordan Population and Family Health Survey (JPFHS) is a national sample survey carried out by the Department of Statistics (DOS) as part of its National Household Surveys Program (NHSP). The JPFHS was specifically aimed at providing information on fertility, family planning, and infant and child mortality. Information was also gathered on breastfeeding, on maternal and child health care and nutritional status, and on the characteristics of households and household members. The survey will provide policymakers and planners with important information for use in formulating informed programs and policies on reproductive behavior and health.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

The 1997 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, for urban and rural areas, for the three regions (each composed of a group of governorates), and for the three major governorates, Amman, Irbid, and Zarqa.

The 1997 JPFHS sample is a subsample of the master sample that was designed using the frame obtained from the 1994 Population and Housing Census. A two-stage sampling procedure was employed. First, primary sampling units (PSUs) were selected with probability proportional to the number of housing units in the PSU. A total of 300 PSUs were selected at this stage. In the second stage, in each selected PSU, occupied housing units were selected with probability inversely proportional to the number of housing units in the PSU. This design maintains a self-weighted sampling fraction within each governorate.

UPDATING OF SAMPLING FRAME

Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings and housing units were updated, listed and documented, along with the name of the owner/tenant of the unit or household and the name of the household head. These activities took place between January 7 and February 28, 1997.

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

Mode of data collection

Face-to-face

Research instrument

The 1997 JPFHS used two questionnaires, one for the household interview and the other for eligible women. Both questionnaires were developed in English and then translated into Arabic. The household questionnaire was used to list all members of the sampled households, including usual residents as well as visitors. For each member of the household, basic demographic and social characteristics were recorded and women eligible for the individual interview were identified. The individual questionnaire was developed utilizing the experience gained from previous surveys, in particular the 1983 and 1990 Jordan Fertility and Family Health Surveys (JFFHS).

The 1997 JPFHS individual questionnaire consists of 10 sections: - Respondent’s background - Marriage - Reproduction (birth history) - Contraception - Pregnancy, breastfeeding, health and immunization - Fertility preferences - Husband’s background, woman’s work and residence - Knowledge of AIDS - Maternal mortality - Height and weight of children and mothers.

Cleaning operations

Fieldwork and data processing activities overlapped. After a week of data collection, and 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.

Data entry started after a week of office data processing. The process of data entry, editing, and cleaning was done by means of the ISSA (Integrated System for Survey Analysis) program DHS has developed especially for such surveys. The ISSA program allows data to be edited while being entered. Data entry was completed on November 14, 1997. A data processing specialist from Macro made a trip to Jordan in November and December 1997 to identify problems in data entry, editing, and cleaning, and to work on tabulations for both the preliminary and final report.

Response rate

A total of 7,924 occupied housing units were selected for the survey; from among those, 7,592 households were found. Of the occupied households, 7,335 (97 percent) were successfully interviewed. In those households, 5,765 eligible women were identified, and complete interviews were obtained with 5,548 of them (96 percent of all eligible women). Thus, the overall response rate of the 1997 JPFHS was 93 percent. The principal reason for nonresponse among the women was the failure of interviewers to find them at home despite repeated callbacks.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are subject to two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the result of mistakes made in implementing data collection and data processing (such as failure to locate and interview the correct household, misunderstanding questions either by the interviewer or the respondent, and data entry errors). Although during the implementation of the 1997 JPFHS numerous efforts were made to minimize this type of error, nonsampling errors are not only impossible to avoid but also difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The respondents selected in the 1997 JPFHS constitute only one of many samples that could have been selected from the same population, given the same design and expected size. Each of those samples would have yielded results differing somewhat from the results of the sample actually 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.

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, since the 1997 JDHS-II sample resulted from a multistage stratified design, formulae of higher complexity had to be used. The computer software used to calculate sampling errors for the 1997 JDHS-II was the ISSA Sampling Error Module, which uses the Taylor linearization method of 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.

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

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

About this dataset

Context

The dataset tabulates the population of Rutherford College by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Rutherford College across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.26% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Rutherford College is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Rutherford College total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rutherford College Population by Race & Ethnicity. You can refer the same here

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The cultural tourism market report provides a detailed Porter’s Five Forces Analysis for the forecast period.

The data provides information that will help the vendors strategize their business plans and guide them to have a better understanding of the competitive landscape. To gain more insights on Porter’s Five Forces Analysis request for a sample of the report.

HCE: Number of Sample Households Reporting Consumption: Manipur: Rural: Food: Salt data was reported at 1,360.000 Unit in 2012. This records a decrease from the previous number of 1,368.000 Unit for 2010. HCE: Number of Sample Households Reporting Consumption: Manipur: Rural: Food: Salt data is updated yearly, averaging 1,364.000 Unit from Jun 1994 (Median) to 2012, with 4 observations. The data reached an all-time high of 2,173.000 Unit in 2005 and a record low of 998.000 Unit in 1994. HCE: Number of Sample Households Reporting Consumption: Manipur: Rural: Food: Salt data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB058: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Manipur: Rural (Discontinued).

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives The 2006 Thailand Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Thailand; - To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals (MDG), the goals of A World Fit for Children (WFFC) and other internationally agreed upon goals, as a basis for future action at national and provincial level; and - To contribute to the improvement of data and monitoring systems on the situation of children and women in Thailand and strengthening technical expertise for the design, implementation, and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was implemented by the National Statistical Office of Thailand, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

Geographic coverage

The survey was designed to produce estimates for indicators at the national level, by urban and rural disaggregation, for each of the 4 regions of Thailand (North, Northeast, Central, and South) and by individual province for 26 (out of 76 total) targeted provinces (note: additional data collections were performed for the targeted provinces during March-May 2006; separate results publications for each province are pending).

Analysis unit

• Households
• Women aged 15-49
• Children under 5 years of age

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Thailand Multiple Indicator Cluster Survey (MICS) was carried out by a sample survey method that used a stratified two stage sampling plan. The primary sample units (PSUs) consisted of blocks (in municipal areas) or villages (in non-municipal areas). The secondary sample units consisted of collective households systematically drawn from a household listing. The plan is designed to provide estimates of situation indicators for children and women at the national level, for municipal and non-municipal areas, and for four regions: Central (including Bangkok), North, Northeast and South. The household listing is obtained from The Basic Household Information Survey conducted every two years by the National Statistical Office (NSO). In the survey, members of each household located in the block/village samples are counted.

Data on basic household information from the survey are to be used as the sample frame in various survey projects of the NSO. Data from the 2006 Basic Household Information Survey were used as the frame for household samples in the Thailand MICS. Thirty collective household samples per block/village sample were selected in both municipal and non-municipal areas. Field staff then created a Listing of Household Samples by adding together all the names of household heads and the addresses. After a household listing was carried out within the selected 30 households in each block/village, a systematic sample of households was drawn. For national-level results, sample data were weighted in accordance with sampling plan.

A block is an operational boundary in a municipal area that is made up of approximately 100 to 200 households. Blocks are established on a map so that field staff know the exact area they are to cover in the survey.

A village is an administrative unit, a community, in a non-municipal area governed by a village head (Phuyaiban) or a district head (Kamnan).

The MICS national-level report included 1,449 block/village samples. Thirty collective household samples per block/village samples were selected and a total of 43,470 household samples were obtained.

For MICS provincial-level reports, 1,032 block/village samples were selected and 30,960 household samples were included.

More detailed information on the sample design is available in Appendix A of the Survey Final Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Thailand MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.

The questionnaires were translated into Thai by the NSO MICS coordinators in September 2005.

In addition to the administration of questionnaires, fieldwork teams tested salt used for cooking in the households surveyed for presence of iodine, and measured the weight and height of children under 5 years of age.

Cleaning operations

After the fieldwork, the team supervisor checked the data collected during the interview for completeness. Then the Provincial Statistical Officer in each province and the Director of the Data Management Division of the Bangkok Metropolitan Administration randomly rechecked the data before sending all the questionnaires to the National Statistical Office (NSO) for processing.

Upon receiving the questionnaires from the 76 provinces, the collected data were entered on 30 microcomputers by data entry operators and data entry supervisors at the Thai NSO, using CSPro software. In order to ensure quality control, editing and structural checks, all questionnaires were double entered for verification and internal consistency checks were performed, followed by secondary editing. The data entry and verification used CSPro programme applications that were developed under the global Multiple Indicator Cluster Survey (MICS) project by UNICEF to be used as standard processing procedures worldwide. In Thailand, the standard CSPro programme was modified appropriately to the Thai version questionnaires. The modification was done by NSO staff that had been trained on data processing by MICS experts from UNICEF.

Data entry and data verification for the national level report began in February 2006 and was completed in April 2006. For the provincial reports, the process was completed in June 2006. Data were analysed using the Statistical Package for Social Sciences (SPSS) software programme, Version 14, and the model syntax and tabulation plans developed by UNICEF for this purpose.

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Response rate

Of the 43,440 households selected for the sample, 42,302 were found to be occupied. Of these, 40,511 were successfully interviewed, yielding a response rate of 95.8 percent. In the interviewed households, 37,187 eligible women (aged 15-49) were identified. Of these eligible women, 36,960 were successfully interviewed, yielding a response rate of 99.4 percent. In addition, 9,444 children under the age of 5 were listed as being eligible in the households. The mothers and/or caretakers of 9,409 of these children (99.6 per cent) were successfully interviewed.

Differentials in response rates by areas showed 94.9 percent of the households in municipal areas and 96.9 percent in non-municipal areas. Participant differentials in response rates were observed, with the highest in the North Region (98.8 percent), followed by the Northeast Region (98.1 percent), and the South and the Central regions' same low response rate of 93 percent.

Sampling error estimates

The sample of respondents selected in the Thailand Multiple Indicator Cluster Survey (MICS) is only one of the samples that could have been selected from the same population, using the same design and 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 between all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey results.

The

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular.

MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives The 2005 Serbia Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Serbia. - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Serbia and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was carried out by the Statistical Office of the Republic of Serbia and the Strategic Marketing Research Agency, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

In 2005 Serbia and Montenegro was the State Union composed of the Republic of Serbia (92.5% of population) and the Republic of Montenegro (7.5% of total population). The MICS 2005 survey was planned and implemented on the whole territory of Serbia and Montenegro, and all documents regarding survey plan and contracts with implementing agencies covered the State Union. In May, 2006 the Republic of Montenegro had a referendum of independency and the State Union broke apart. The results of MICS 2005 survey were presented separately for both countries and two separate reports were prepared.

The survey was implemented by the Statistical Office of the Republic of Serbia (in Serbia) and the Statistical Office of the Republic of Montenegro (in Montenegro) and the expert research agency - Strategic Marketing & Media Research Institute (SMMRI), which covered the survey implementation in both Serbia and Montenegro.

Special tasks performed by the Statistical Office of the Republic of Serbia: Preparation of questionnaire for the survey: Preparation of methodological guidelines for realization of the survey; Updating of lists of households in the selected census block units; Conducting the pilot ; Selection of households to be covered by sample; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Special tasks performed by the SMMRI: Sample selection; Preparation of survey tools; Organising the training; Conducting the pilot; Updating of lists of households in the selected census block units; Organising field work; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Data processing and analysis; Preparation of report.

Geographic coverage

The sample for the Serbia Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for urban and rural areas, and for six regions: Vojvodina, Belgrade, West, Central, East and South-East Serbia. Belgrade has a large population (almost one-quarter of the total) and its predominantly urban characteristics make it necessary to separate it from the rest of Central Serbia, to which it administratively belongs. In order to look more deeply into existing ethnic disparities and to provide national estimates, a separate sample was designed for Roma living in Roma settlements.

Analysis unit

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 6 regions (Vojvodina, Belgrade, West, Central, East and South-East Serbia) for key indicators. Separate sample was designed for Roma living in Roma settlements.

Important factors which influenced the sample design of both Serb and Roma samples are the fertility rate and number of household members.

A stratified, two-stage random sampling approach was used for the selection of the survey sample.

In the case of the Serbia without the Roma settlements sample, 400 census enumeration areas within each region with probability proportional to size were selected during the first stage. Since the sample frame (Census 2002) was not up to date, household lists in all selected enumeration areas were updated prior to the selection of households. Owing to the low fertility rate and small household size, households were stratified into two categories. One category of households consists of households with under 5 children, while the other category consists of households without children under 5. The allocation of the sample in the category of households with children was significantly greater than the allocation of the sample in the category of households without children. Based on the updated information, selected units were divided into clusters of 18 households on average, plus 3 backup households. Backup households were interviewed only if some of the first 18 households were not found. In the event that a household refused to be interviewed, a backup household was not contacted. In each cluster, the number of households with children was selected with probability proportional to size.

In the case of the Roma population, the universe could be defined only for Roma who live in separate settlements. During the first stage, 106 census enumeration areas were selected. The updating of household lists was done prior to household selection, but there was no need for sample stratification of households with and without children under 5. The average number of households selected in each cluster was 18 on average, plus 3 backup households.

Secondly, after the household listing was carried out within the selected enumeration areas, a systematic sample of 7,794 households in Serbia without Roma from Roma settlements and 1,959 Roma households was drawn up, which makes a total of 9,953 sampled households.

The 2002 Serbian Population Census framework was used for the selection of clusters. Census enumeration areas (app. 100 households) were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2002 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the 6 regions by urban and rural areas separately.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

The Serbia Multiple Indicator Cluster Survey sample is not self-weighted. For reporting of national level results,

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Abstract

In 2010, the EU-SILC instrument covered 32 countries, that is, all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 6th version of the 2010 Cross-Sectional User Database as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

About this dataset

Context

The dataset tabulates the population of Rutherford College by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Rutherford College. The dataset can be utilized to understand the population distribution of Rutherford College by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Rutherford College. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Rutherford College.

Key observations

Largest age group (population): Male # 60-64 years (98) | Female # 30-34 years (70). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Rutherford College population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Rutherford College is shown in the following column.
• Population (Female): The female population in the Rutherford College is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Rutherford College for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rutherford College Population by Gender. You can refer the same here

Abstract

The Government of Iraq, with support from UNICEF finalized and launched a Multiple Indicator Cluster Survey (MICS 6) in 2018. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Data and information from MICS6 provides credible and reliable evidence for the Government of Iraq to monitor the National Development Plan and establish baselines and monitor progress towards Sustainable Development Goals (SGDs). It helps the government and its stakeholders to understand disparities and the wider development challenges in the country.

The 2018 Iraq MICS has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Iraq;

• To furnish data needed for monitoring progress towards national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention.

Geographic coverage

The sample for the Iraq MICS 2018 was designed to provide estimates at the national, regional and governorates level, for urban and rural areas. Specifically the sample for the Iraq MICS 2018 survey includes 2 regions - Kurdistan and South/Central Iraq and 18 governorates - Duhok, Nainawa, Sulaimaniya, Kirkuk, Erbil, Diala, Anbar, Baghdad, Babil, Karbalah, Wasit, Salahaddin, Najaf, Qadissiyah, Muthana, Thiqar, Musan, and Basra.

Analysis unit

• Individuals

• Households

Universe

The MICS survey considers the households and their members in all urban and rural areas of Iraq as the Universe. Thus, the Universe for Iraq consists of all persons in the country residing in various geographic locations considering all special ethnic or economic groups in the rural and urban areas of Iraq. For the purposes of this survey, Internally Displaced Persons living in United Nations/government notified camps, military installations, and non-residential units such as business establishments were not considered in the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The last census in Iraq was carried out in 1998 and the sampling frame was developed during that time. The most recent update of this sampling frame was done in 2009 which was used by Central Statistical Office (CSO) for the selection of the Clusters in Iraq region. On the other hand, the Kurdistan Region Statistical Office (KRSO) has updated the 2009 sampling frame for the 3 main cities of Kurdish region and their periphery and used it to draw the Clusters. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs). A listing of households was conducted in each sample EA, and a sample of households was selected at the second stage.

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size has been calculated using the prevalence rates of key indicators from the 2011 MICS. For the purpose of identifying the optimal sample size for 2018 MICS, all the factors such as time, cost, domain of estimation, sampling and non-sampling errors were taken into account, as well as the desired level of precision of the key prevalence indicator. The sample size was calculated at the governorate level. It was decided that 2018 MICS will provide the estimates at the governorate level, so the indicative sample size has been calculated using governorate as the domain for the geographic representation. The formula for calculating the sample size is described in Appendix A of report available in related materials.

A number of meetings were held in the CSO to finalize the sample size, and various refinements were studied using the referred formula. As a result of these discussions the MICS Technical Committee reached a consensus on a sample size of 1,080 households for each governorate of Iraq, where each governorate was divided into 90 sample clusters and 12 households were selected per cluster (90 clusters x 12 households = 1,080 households). Baghdad was sub-divided into two administrative areas, therefore 19 total individual domains were used for a total sample size of 20,520 households (19 domains x 1,080 households).

One-third of the sampled households was selected for water quality testing, which means 360 households per governorate or 6,840 (360 X 19) households for the overall survey. The subsample of 4 households for the water quality testing in each cluster are selected using systematic random sampling.

Each Governorate is further stratified into urban and rural areas, and the sample within each governorate is allocated proportionately to the urban and rural strata based on the population. The urban and rural areas within each governorate are the main sampling strata. Within each stratum, a specified number of clusters is selected systematically using probability proportionate to size (PPS) sampling methodology. After the selection of the clusters in each rural and urban stratum, a new listing of households was conducted in each sample cluster. Then a systematic random sample of 12 households per cluster is drawn from the listing for each rural and urban sample cluster.

SELECTION OF ENUMERATION AREAS (CLUSTERS):

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the Iraq 2009 sampling frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the 19 sampling domains, separately for the urban and rural strata. However, there are a few areas belonging to two governorates that were not accessed due to security reasons. These governorates are Nainawa and Kirkuk. In Nainawa 5 districts were excluded (Ba'aj, Al-Hadar, Telafer, Sinjar and Makhmoor), while only Haweja district in Kirkuk was excluded. The excluded districts represent around 22% of the urban population and 51% of the rural population in Nainawa. The percentage of not accessed area in final sample for Kirkuk represents 5% of the Urban and 42% of the rural population, following the exclusion of Haweja district.

SELECTION OF HOUSEHOLDS:

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 12 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

The Iraq 2018 MICS also included water quality testing for a subsample of households within each sample cluster. A subsample of 4 of the 12 selected households was selected in each sample cluster using random systematic sampling for conducting water quality testing, for both water in the household and at the source, including a chlorine test. The MICS6 household selection template includes an option to specify the number of households to be selected for the water quality testing, and the spreadsheet automatically selected the corresponding subsample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 5) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the MICS6 standard questionnaires. From the MICS6 model Arabic version, the questionnaires were customised and translated to two Kurdish dialects and were pre-tested in 3 governorates (Baghdad, Najaf and Basra) in South/Central Iraq region and 3 governorates (Duhok, Erbil & Sulaimaniya) in Kurdistan region of Iraq during Dec 2017/Jan 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were received at the Central Statistical Organization (CSO) via Internet File Streaming System (IFSS), integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in details in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data

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