The East Asian Social Survey (EASS) is a biennial social survey project that serves as a cross-national network of the following four General Social Survey type surveys in East Asia: Chinese General Social Survey (CGSS), Japanese General Social Survey (JGSS), Korean General Social Survey (KGSS), Taiwan Social Change Survey (TSCS), and comparatively examines diverse aspects of social life in these regions. Survey information in this module focuses on family dynamics and includes demographic variables such as the number of family members, the number of younger and older siblings, the number of sons and daughters, and whether family members are alive or deceased. Respondents were also queried about specific information pertaining to family members and children not co-residing with them, such as, sex and birth order, age, marital status, residence status, contact frequency, employment status, and relation to the respondent. Other information collected includes attitudes toward financial support from family members and how frequently financial and personal support was provided. Questions also include opinions regarding household chores, lifestyle preferences, health of respondent and parents, as well as family obligations. Quality of life questions addressed how satisfied respondents were as well as overall marital happiness. Demographic information specific to the respondent and their spouse includes age, sex, marital status, education, employment status and hours worked, occupation, earnings and income, religion, class, size of community, and region.

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 data on relationship to householder were derived from answers to Question 2 in the 2015 American Community Survey (ACS), which was asked of all people in housing units. The question on relationship is essential for classifying the population information on families and other groups. Information about changes in the composition of the American family, from the number of people living alone to the number of children living with only one parent, is essential for planning and carrying out a number of federal programs.

The responses to this question were used to determine the relationships of all persons to the householder, as well as household type (married couple family, nonfamily, etc.). From responses to this question, we were able to determine numbers of related children, own children, unmarried partner households, and multi-generational households. We calculated average household and family size. When relationship was not reported, it was imputed using the age difference between the householder and the person, sex, and marital status.

Household – A household includes all the people who occupy a housing unit. (People not living in households are classified as living in group quarters.) A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other people in the building and which have direct access from the outside of the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated people who share living arrangements.

Average Household Size – A measure obtained by dividing the number of people in households by the number of households. In cases where people in households are cross-classified by race or Hispanic origin, people in the household are classified by the race or Hispanic origin of the householder rather than the race or Hispanic origin of each individual.

Average household size is rounded to the nearest hundredth.

Comparability – The relationship categories for the most part can be compared to previous ACS years and to similar data collected in the decennial census, CPS, and SIPP. With the change in 2008 from “In-law” to the two categories of “Parent-in-law” and “Son-in-law or daughter-in-law,” caution should be exercised when comparing data on in-laws from previous years. “In-law” encompassed any type of in-law such as sister-in-law. Combining “Parent-in-law” and “son-in-law or daughter-in-law” does not represent all “in-laws” in 2008.

The same can be said of comparing the three categories of “biological” “step,” and “adopted” child in 2008 to “Child” in previous years. Before 2008, respondents may have considered anyone under 18 as “child” and chosen that category. The ACS includes “foster child” as a category. However, the 2010 Census did not contain this category, and “foster children” were included in the “Other nonrelative” category. Therefore, comparison of “foster child” cannot be made to the 2010 Census. Beginning in 2013, the “spouse” category includes same-sex spouses.

ABOUT THE COMMUNITY SURVEY DATASET

Final Reports for ETC Institute conducted annual community attitude surveys for the City of Tempe. These survey reports help determine priorities for the community as part of the City's on-going strategic planning process.

In many of the survey questions, survey respondents are asked to rate their satisfaction level on a scale of 5 to 1, where 5 means "Very Satisfied" and 1 means "Very Dissatisfied" (while some questions follow another scale). The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.

This data is the weighted data provided by the ETC Institute, which is used in the final published PDF report.

PERFORMANCE MEASURES

Data collected in these surveys applies directly to a number of performance measures for the City of Tempe including the following (as of 2021):

1. Safe and Secure Communities

• 1.04 Fire Services Satisfaction
• 1.06 Victim Not Reporting Crime to Police
• 1.07 Police Services Satisfaction
• 1.09 Victim of Crime
• 1.10 Worry About Being a Victim
• 1.11 Feeling Safe in City Facilities
• 1.23 Feeling of Safety in Parks

2. Strong Community Connections

• 2.02 Customer Service Satisfaction
• 2.04 City Website Quality Satisfaction
• 2.05 Online Services Satisfaction Rate
• 2.15 Feeling Invited to Participate in City Decisions
• 2.21 Satisfaction with Availability of City Information

3. Quality of Life

• 3.16 City Recreation, Arts, and Cultural Centers
• 3.17 Community Services Programs
• 3.19 Value of Special Events
• 3.23 Right of Way Landscape Maintenance
• 3.36 Quality of City Services

4. Sustainable Growth & Development

• No Performance Measures in this category presently relate directly to the Community Survey

5. Financial Stability & Vitality

• No Performance Measures in this category presently relate directly to the Community Survey

Additional Information

Source: Community Attitude Survey

Contact (author): Wydale Holmes

Contact E-Mail (author): wydale_holmes@tempe.gov

Contact (maintainer): Wydale Holmes

Contact E-Mail (maintainer): wydale_holmes@tempe.gov

Data Source Type: Excel table

Preparation Method: Data received from vendor

Publish Frequency: Annual

Publish Method: Manual

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation. The first survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys. The current survey, HIECS 2012/2013, is the eleventh in this long series. Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. This would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households. CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To define average household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index. - To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household. - To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

Compared to previous surveys, the current survey experienced certain peculiarities, among which : 1) The total sample of the current survey (24.9 thousand households) is divided into two sections: a -A new sample of 16.1 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, etc.
b -A panel sample of 2008/2009 survey data of around 8.8 thousand households were selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2) Some additional questions that showed to be important based on previous surveys results, were added to the survey questionnaire, such as: a - The extent of health services provided to monitor the level of services available in the Egyptian society. By collecting information on the in-kind transfers, the household received during the year; in order to monitor the assistance the household received from different sources government, association,..etc. b - Identifying the main outlet of fabrics, clothes and footwear to determine the level of living standards of the household.

3) Quality control procedures especially for fieldwork are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment.

Geographic coverage

National coverage, covering a sample of urban and rural areas in all the governorates.

Analysis unit

• Household/family
• Individual/person

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS 2012/2013 is a self-weighted two-stage stratified cluster sample, of around 24.9 households. The main elements of the sampling design are described in the following:

Sample Size The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 24863 households has been considered, and was distributed between urban and rural with the percentages of 45.4 % and 54.6, respectively. This sample is divided into two parts: a) A new sample of 16094 households selected from main enumeration areas. b) A panel sample of 8769 households (selected from HIECS 2010/2011 and the preceding survey in 2008/2009).

Cluster Size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 8 households (In HIECS 2011/2012 a cluster size of 16 households was used). While the cluster size for the panel sample was 4 households.

Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2012 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

New Households Sample: 1000 sample areas were selected across all governorates (urban/rural) using a proportional technique with the sample size. The number required for each governorate (urban/rural) was selected from the enumeration areas of the core sample using a systematic sampling technique.A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Sampling deviation

Given the sample design, these weights will vary to some extent for the over-sampled governorates compared with the others. It is also important to calculate measures of sampling variability for key survey estimates.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1) Expenditure and Consumption Questionnaire. 2) Diary Questionnaire (Assisting questionnaire).

Analysis of ‘City of Tempe 2021 Community Survey Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/8b86f64f-8545-4f29-b5b5-35e5366538ed on 11 February 2022.

--- Dataset description provided by original source is as follows ---

ABOUT THE COMMUNITY SURVEY DATASET

Final Reports for ETC Institute conducted annual community attitude surveys for the City of Tempe. These survey reports help determine priorities for the community as part of the City's on-going strategic planning process.

In many of the survey questions, survey respondents are asked to rate their satisfaction level on a scale of 5 to 1, where 5 means "Very Satisfied" and 1 means "Very Dissatisfied" (while some questions follow another scale). The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.

This data is the weighted data provided by the ETC Institute, which is used in the final published PDF report.

PERFORMANCE MEASURES

Data collected in these surveys applies directly to a number of performance measures for the City of Tempe including the following (as of 2021):

1. Safe and Secure Communities

• 1.04 Fire Services Satisfaction
• 1.06 Victim Not Reporting Crime to Police
• 1.07 Police Services Satisfaction
• 1.09 Victim of Crime
• 1.10 Worry About Being a Victim
• 1.11 Feeling Safe in City Facilities
• 1.23 Feeling of Safety in Parks

2. Strong Community Connections

• 2.02 Customer Service Satisfaction
• 2.04 City Website Quality Satisfaction
• 2.05 Online Services Satisfaction Rate
• 2.15 Feeling Invited to Participate in City Decisions
• 2.21 Satisfaction with Availability of City Information

3. Quality of Life

• 3.16 City Recreation, Arts, and Cultural Centers
• 3.17 Community Services Programs
• 3.19 Value of Special Events
• 3.23 Right of Way Landscape Maintenance
• 3.36 Quality of City Services

4. Sustainable Growth & Development

• No Performance Measures in this category presently relate directly to the Community Survey

5. Financial Stability & Vitality

• No Performance Measures in this category presently relate directly to the Community Survey

Additional Information

Source: Community Attitude Survey

Contact (author): Wydale Holmes

Contact E-Mail (author): wydale_holmes@tempe.gov

Contact (maintainer): Wydale Holmes

Contact E-Mail (maintainer): wydale_holmes@tempe.gov

Data Source Type: PDF

Preparation Method: Data received from vendor

Publish Frequency: Annual

Publish Method: Manual

--- Original source retains full ownership of the source dataset ---

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.

These data are being released in BETA version to facilitate early access to the study for research purposes. This collection has not been fully processed by NACDA or ICPSR at this time; the original materials provided by the principal investigator were minimally processed and converted to other file types for ease of use. As the study is further processed and given enhanced features by ICPSR, users will be able to access the updated versions of the study. Please report any data errors or problems to user support and we will work with you to resolve any data related issues. The National Health Interview Survey (NHIS) is conducted annually and sponsored by the National Center for Health Statistics (NCHS), which is part of the U.S. Public Health Service. The purpose of the NHIS is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive across the United States population through the collection and analysis of data on a broad range of health topics. The redesigned NHIS questionnaire introduced in 1997 (see National Health Interview Survey, 1997 [ICPSR 2954]) consists of a core that remains largely unchanged from year to year, plus an assortment of supplements varying from year to year. The 2010 NHIS Core consists of three modules: Family, Sample Adult, and Sample Child. The datasets derived from these modules include Household Level, Family Level, Person Level, Injury/Poison Episode Level, Injury/Poison Verbatim Level, Sample Adult Level, and Sample Child level. The 2010 NHIS supplements consist of stand alone datasets for Cancer Level and Quality of Life data derived from the Sample Adult core and Disability Questions Tests 2010 Level derived from the Family core questionnaire. Additional supplementary questions can be found in the Sample Child dataset on the topics of cancer, immunization, mental health, and mental health services and in the Sample Adult dataset on the topics of epilepsy, immunization, and occupational health. Part 1, Household Level, contains data on type of living quarters, number of families in the household responding and not responding, and the month and year of the interview for each sampling unit. Parts 2-5 are based on the Family Core questionnaire. Part 2, Family Level, provides information on all family members with respect to family size, family structure, health status, limitation of daily activities, cognitive impairment, health conditions, doctor visits, hospital stays, health care access and utilization, employment, income, participation in government assistance programs, and basic demographic information. Part 3, Person Level, includes information on sex, age, race, marital status, education, family income, major activities, health status, health care costs, activity limits, and employment status. Parts 4 and 5, Injury/Poisoning Episode Level and Injury/Poisoning Verbatim Level, consist of questions about injuries and poisonings that resulted in medical consultations for any family members and contains information about the external cause and nature of the injury or poisoning episode and what the person was doing at the time of the injury or poisoning episode, in addition to the date and place of occurrence. A randomly-selected adult in each family was interviewed for Part 6, Sample Adult Level, regarding specific health issues, the relation between employment and health, health status, health care and doctor visits, limitation of daily activities, immunizations, and behaviors such as smoking, alcohol consumption, and physical activity. Demographic information, including occupation and industry, also was collected. The respondents to Part 6 also completed Part 7, Cancer Level, which consists of a set of supplemental questions about diet and nutrition, physical activity, tobacco, cancer screening, genetic testing, family history, and survivorship. Part 8, Sample Child Level, provides information from an adult in the household on medical conditions of one child in the household, such as developmental or intellectual disabilities, respiratory problems, seizures, allergies, and use of special equipment like hearing aids, braces, or wheelchairs. Parts 9 through 13 comprise the additional Supplements and Paradata for the 2010 NHIS. Part 9, Disability Questions Tests 2010 Level

Abstract

The surveys is designed to collect, analyze and disseminate demographic and health data pertaining to the Palestinian population living in the Palestinian Territory, with a focus on demography, fertility, family planning and maternal and child health, in addition to youth and elderly. The 2006 survey also includes new sections and elements, such as basic health and socio-economic information on different groups within the population, and children less than five years, and children aged 2-14 years, children aged 5-17 years in addition to un-married youth aged 15-29 years and elderly people aged 60 years and over. It is hoped that by gradually introducing new sections into the Palestinian Family Health Survey, it can be transformed into a survey of all of the population.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates

Analysis unit

Household, individual

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample frame and sample design: The list of all Palestinian households has been constructed from the updated frame in 2003. The master sample was drawn to be used for different surveys.

The sample type was a stratified two-stage random sample: First stage: 325 EAs were selected from all Palestinian Territory. Second stage: A systematic random sample of 40 households was selected from each enumeration Area (EA) in the West Bank and Gaza Strip.

Due to the privacy of this survey, each EA was divided into two cells, the first one with 21 households while the other with 19 households. The first cell was prepared to collect the PAPFAM and MICS indicators, while the second was prepared to collect the MICS indicators only. It is worth to mention that there is no crosscutting between the two groups.

In this survey all un-married youth aged 15-29 years and elder persons aged 60 years and over were enumerated, in addition, one child out of all children aged 2-14 years in each household was selected for child discipline part using Kish Table.

Sample size: The number of the households in the sample was 13,238 households: 8,781 in the West Bank and 4,457 in Gaza Strip.

Mode of data collection

Face-to-face [f2f]

Research instrument

In this survey four questionnaires were used:

The first questionnaire: This questionnaire was designed to collect PAPFAM and MICS indicators together, and it was collected from about 7,056 households. The questionnaire was consisted of the following parts:

• Household part: consisted household roster including demographic variables such as age, sex, date of birth, smoking, labor force status, education variables, disability, chronic diseases and others. In addition to child discipline section for children aged 2-14 years, child labor for children aged 5-17 years and education section for persons aged 5-24 years.
• Dwelling part: including questions on housing conditions such as main drinking water source, iodized salt and other socio-economic indicators.
• Women part: this part was designed to collect data from all ever-married women 15-54 years old. It consists of seven sections: Women general characteristics, Reproduction, Maternal care, Family planning and Desire for reproduction, Tetanus toxoid vaccination, Knowledge of STDs, Chronic disease and disease due to reproduction.
• Child part: this part was designed to collect data from all children aged less than 5 years, it consists of four sections: Child health and vaccinations, Early education, Birth registration, and Anthropometric measurements.

The second questionnaire: This questionnaire was designed to collect MICS indicators only; it is part of the first one. It was collected from about 6,182 households. The questionnaire was consisted of all the parts mentioned above except: Chronic diseases in household part, and Knowledge of STDs in women part. This methodology was used in order to disseminate the data on these indicators at the governorate level.

The third questionnaire: This questionnaire was designed to collect data from all un- married youth aged 15-29 years.

The fourth questionnaire: This questionnaire was designed to collect data from all elderly persons aged 60 years and over.

Cleaning operations

Data editing took place at a number of stages through the processing including:

1. office editing and coding
2. during data entry
3. structure checking and completeness
4. structural checking of SPSS data files

Response rate

The survey sample consists of about 13,238 households of which 11,661 households completed the interview; whereas 7,700 households from the West Bank and 3,961 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 85.5% while in the Gaza Strip it reached 93.1%. The response rate in the Palestinian Territory reached 88.0%.

Sampling error estimates

Detailed information on the sampling Error is available in the Survey Report.

Data appraisal

Detailed information on the data appraisal is available in the Survey Report.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The HIECS 2008/2009 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2008/2009, among a long series of similar surveys that started back in 1955.

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To measure mean household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To define mean household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependant on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income and expenditure for commodities and services. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its sources and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to sources, either from household production or not, in addition to household expenditure for non food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ...) in urban and rural areas. - To identify the percentage distribution of income recipients according to some background variables such as housing conditions, size of household and characteristics of head of household.

Compared to previous surveys, the current survey experienced certain peculiarities, among which: 1- Doubling the number of area segments from 1200 in the previous survey to 2526 segments with decreasing the number of households selected from each segment to be (20) households instead of (40) in the previous survey to ensure appropriate representatives in the society. 2- Changing the survey period to 15 days instead of one month in the previous one 200412005, to lighten the respondent burden and encourage more cooperation. 3- Adding some additional questions: a- Participation or the benefits gained from pension and social security system. b- Participation in health insurance system. 4- Increasing quality control Procedures especially for fieldwork to ensure data accuracy and avoid any errors in suitable time.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS, 2008-2009 is a two-stage stratified cluster sample, approximately self-weighted, of nearly 48000 households. The main elements of the sampling design are described in the following.

1- Sample Size
It has been deemed important to retain the same sample size of the previous two HIECS rounds. Thus, a sample of about 48000 households has been considered. The justification of maintaining the sample size at this level is to have estimates with levels of precision similar to those of the previous two rounds: therefore trend analysis with the previous two surveys will not be distorted by substantial changes in sampling errors from round to another. In addition, this relatively large national sample implies proportional samples of reasonable sizes for smaller governorates. Nonetheless, over-sampling has been introduced to raise the sample size of small governorates to about 1000 households As a result, reasonably precise estimates could be extracted for those governorates. The over-sampling has resulted in a slight increase in the national sample to 48658 households.

2- Cluster size
An important lesson learned from the previous two HIECS rounds is that the cluster size applied in both surveys is found to be too large to yield an accepted design effect estimates. The cluster size was 40 households in the 2004-2005 round, descending from 80 households in the 1999-2000 round. The estimates of the design effect (deft) for most survey measures of the latest round were extraordinary large. As a result, it has been decided to decrease the cluster size to only 19 households (20 households in urban governorates to account for anticipated non-response in those governorates: in view of past experience non-response is almost nil in rural governorates).

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among the documentation materials published in both Arabic and English.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1- Expenditure and consumption questionnaire. 2- Diary questionnaire for expenditure and consumption. 3- Income questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of Labor Statisticians held in Geneva, 2003. - Using the recent Classification of Individual Consumption according to Purpose (COICOP). - Using more than one approach of expenditure measurement to serve many purposes of the survey.

A brief description of each questionnaire is given next:

1- Expenditure and Consumption Questionnaire

This questionnaire comprises 14 tables in addition to identification and geographic data of household on the cover page. The questionnaire is divided into two main sections.

Section one: Household schedule and other information. It includes: - Demographic characteristics and basic data for all household individuals consisting of 18 questions for every person. - Members of household who are currently working abroad. - The household ration card. - The main outlets that provide food and beverage. - Domestic and foreign tourism. - The housing conditions including 15 questions. - Means of transportation used to go to work or school. - The household possession of appliances and means of transportation. - This section includes some questions which help to define the social and economic level of households which in turn, help interviewers to check the plausibility of expenditure, consumption and income data.

Section two: Expenditure and consumption data It includes 14 tables as follows: - The quantity and value of food and beverages commodities actually consumed. - The quantity and value of the actual consumption of alcoholic beverages, tobacco and narcotics. - The quantity and value of the clothing and footwear. - The household expenditure for housing. - The household expenditure for furnishings, household equipment and routine maintenance of the house. - The household expenditure for health care services. - The household expenditure for transportation. - The household

Abstract

The primary objective of the 2017-18 Jordan Population and Family Health Survey (JPFHS) is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2017-18 JPFHS: - Collected data at the national level that allowed calculation of key demographic indicators - Explored the direct and indirect factors that determine levels of and trends in fertility and childhood mortality - Measured levels of contraceptive knowledge and practice - Collected data on key aspects of family health, including immunisation coverage among children, the prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery among ever-married women - Obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and ever-married women age 15-49 - Conducted haemoglobin testing on children age 6-59 months and ever-married women age 15-49 to provide information on the prevalence of anaemia among these groups - Collected data on knowledge and attitudes of ever-married women and men about sexually transmitted infections (STIs) and HIV/AIDS - Obtained data on ever-married women’s experience of emotional, physical, and sexual violence - Obtained data on household health expenditures

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2017-18 JPFHS is based on Jordan's Population and Housing Census (JPHC) frame for 2015. The current survey is designed to produce results representative of the country as a whole, of urban and rural areas separately, of three regions, of 12 administrative governorates, and of three national groups: Jordanians, Syrians, and a group combined from various other nationalities.

The sample for the 2017-18 JPFHS is a stratified sample selected in two stages from the 2015 census frame. Stratification was achieved by separating each governorate into urban and rural areas. Each of the Syrian camps in the governorates of Zarqa and Mafraq formed its own sampling stratum. In total, 26 sampling strata were constructed. Samples were selected independently in each sampling stratum, through a two-stage selection process, according to the sample allocation. Before the sample selection, the sampling frame was sorted by district and sub-district within each sampling stratum. By using a probability-proportional-to-size selection for the first stage of selection, an implicit stratification and proportional allocation were achieved at each of the lower administrative levels.

In the first stage, 970 clusters were selected with probability proportional to cluster size, with the cluster size being the number of residential households enumerated in the 2015 JPHC. The sample allocation took into account the precision consideration at the governorate level and at the level of each of the three special domains. After selection of PSUs and clusters, a household listing operation was carried out in all selected clusters. The resulting household lists served as the sampling frame for selecting households in the second stage. A fixed number of 20 households per cluster were selected with an equal probability systematic selection from the newly created household listing.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used for the 2017-18 JPFHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect population and health issues relevant to Jordan. After all questionnaires were finalised in English, they were translated into Arabic.

Cleaning operations

All electronic data files for the 2017-18 JPFHS were transferred via IFSS to the DOS central office in Amman, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. Data editing was accomplished using CSPro software. During the duration of fieldwork, 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 October 2017 and completed in February 2018.

Response rate

A total of 19,384 households were selected for the sample, of which 19,136 were found to be occupied at the time of the fieldwork. Of the occupied households, 18,802 were successfully interviewed, yielding a response rate of 98%.

In the interviewed households, 14,870 women were identified as eligible for an individual interview; interviews were completed with 14,689 women, yielding a response rate of 99%. A total of 6,640 eligible men were identified in the sampled households and 6,429 were successfully interviewed, yielding a response rate of 97%. Response rates for both women and men were similar across urban and rural areas.

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 2017-18 Jordan Population and Family Health Survey (JPFHS) 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 2017-18 JPFHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017-18 JPFHS sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF International. These programmes 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.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final 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

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

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Abstract

The 2023 Jordan Population and Family Health Survey (JPFHS) is the eighth Population and Family Health Survey conducted in Jordan, following those conducted in 1990, 1997, 2002, 2007, 2009, 2012, and 2017–18. It was implemented by the Department of Statistics (DoS) at the request of the Ministry of Health (MoH).

The primary objective of the 2023 JPFHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the 2023 JPFHS: • Collected data at the national level that allowed calculation of key demographic indicators • Explored the direct and indirect factors that determine levels of and trends in fertility and childhood mortality • Measured contraceptive knowledge and practice • Collected data on key aspects of family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery • 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 haemoglobin testing with eligible children age 6–59 months and women age 15–49 to gather information on the prevalence of anaemia • Collected data on women’s and men’s knowledge and attitudes regarding sexually transmitted infections and HIV/AIDS • Obtained data on women’s experience of emotional, physical, and sexual violence • Gathered data on disability among household members

The information collected through the 2023 JPFHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Jordan.

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-59, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2023 JPFHS was the 2015 Jordan Population and Housing Census (JPHC) frame. The survey was designed to produce representative results for the country as a whole, for urban and rural areas separately, for each of the country’s 12 governorates, and for four nationality domains: the Jordanian population, the Syrian population living in refugee camps, the Syrian population living outside of camps, and the population of other nationalities. Each of the 12 governorates is subdivided into districts, each district into subdistricts, each subdistrict into localities, and each locality into areas and subareas. In addition to these administrative units, during the 2015 JPHC each subarea was divided into convenient area units called census blocks. An electronic file of a complete list of all of the census blocks is available from DoS. The list contains census information on households, populations, geographical locations, and socioeconomic characteristics of each block. Based on this list, census blocks were regrouped to form a general statistical unit of moderate size, called a cluster, which is widely used in various surveys as the primary sampling unit (PSU). The sample clusters for the 2023 JPFHS were selected from the frame of cluster units provided by the DoS.

The sample for the 2023 JPFHS was a stratified sample selected in two stages from the 2015 census frame. Stratification was achieved by separating each governorate into urban and rural areas. In addition, the Syrian refugee camps in Zarqa and Mafraq each formed a special sampling stratum. In total, 26 sampling strata were constructed. Samples were selected independently in each sampling stratum, through a twostage selection process, according to the sample allocation. Before the sample selection, the sampling frame was sorted by district and subdistrict within each sampling stratum. By using a probability proportional to size selection at the first stage of sampling, an implicit stratification and proportional allocation were achieved at each of the lower administrative levels.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2023 JPFHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Man’s Questionnaire, (4) the Biomarker Questionnaire, and (5) the Fieldworker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Jordan. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After all questionnaires were finalised in English, they were translated into Arabic.

Cleaning operations

All electronic data files for the 2023 JPFHS were transferred via SynCloud to the DoS central office in Amman, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. Data editing was accomplished using CSPro software. During the duration of fieldwork, 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 July and completed in September 2023.

Response rate

A total of 20,054 households were selected for the sample, of which 19,809 were occupied. Of the occupied households, 19,475 were successfully interviewed, yielding a response rate of 98%.

In the interviewed households, 13,020 eligible women age 15–49 were identified for individual interviews; interviews were completed with 12,595 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 6,506 men age 15–59 were identified as eligible for individual interviews and 5,873 were successfully interviewed, yielding a response rate of 90%.

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 in 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 2023 Jordan Population and Family Health Survey (2023 JPFHS) 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 2023 JPFHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2023 JPFHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS 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.

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
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardization exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women
• Heaping in

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2015-2019 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2015-2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

Public use data set on new legal immigrants to the U.S. that can address scientific and policy questions about migration behavior and the impacts of migration. A survey pilot project, the NIS-P, was carried out in 1996 to inform the fielding and design of the full NIS. Baseline interviews were ultimately conducted with 1,127 adult immigrants. Sample members were interviewed at baseline, 6 months, and 12 months, with half of the sample also interviewed at three months. The first full cohort, NIS-2003, is based on a nationally representative sample of the electronic administrative records compiled for new immigrants by the US government. NIS-2003 sampled immigrants in the period May-November 2003. The geographic sampling design takes advantage of the natural clustering of immigrants. It includes all top 85 Metropolitan Statistical Areas (MSAs) and all top 38 counties, plus a random sample of other MSAs and counties. Interviews were conducted in respondents'' preferred languages. The baseline was multi-modal: 60% of adult interviews were administered by telephone; 40% were in-person. The baseline round was in the field from June 2003 to June 2004, and includes in the Adult Sample 8,573 respondents, 4,336 spouses, and 1,072 children aged 8-12. A follow-up was planned for 2007. Several modules of the NIS were designed to replicate sections of the continuing surveys of the US population that provide a natural comparison group. Questionnaire topics include Health (self-reports of conditions, symptoms, functional status, smoking and drinking history) and use/source/costs of health care services, depression, pain; background; (2) Background: Childhood history and living conditions, education, migration history, marital history, military history, fertility history, language skills, employment history in the US and foreign countries, social networks, religion; Family: Rosters of all children; for each, demographic attributes, education, current work status, migration, marital status and children; for some, summary indicators of childhood and current health, language ability; Economic: Sources and amounts of income, including wages, pensions, and government subsidies; type, value of assets and debts, financial assistance given/received to/from respondent from/to relatives, friends, employer, type of housing and ownership of consumable durables. * Dates of Study: 2003-2007 * Study Features: Longitudinal * Sample Size: 13,981

This data collection is comprised of responses from the March and April installments of the 2008 Current Population Survey (CPS). Both the March and April surveys used two sets of questions, the basic CPS and a separate supplement for each month.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment.In addition to the basic CPS questions, respondents were asked questions from the March supplement, known as the Annual Social and Economic (ASEC) supplement. The ASEC provides supplemental data on work experience, income, noncash benefits, and migration. Comprehensive work experience information was given on the employment status, occupation, and industry of persons 15 years old and older. Additional data for persons 15 years old and older are available concerning weeks worked and hours per week worked, reason not working full time, total income and income components, and place of residence on March 1, 2007. The March supplement also contains data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Questions covering training and assistance received under welfare reform programs, such as job readiness training, child care services, or job skill training were also asked in the March supplement.The April supplement, sponsored by the Department of Health and Human Services, queried respondents on the economic situation of persons and families for the previous year. Moreover, all household members 15 years of age and older that are a biological parent of children in the household that have an absent parent were asked detailed questions about child support and alimony. Information regarding child support was collected to determine the size and distribution of the population with children affected by divorce or separation, or other relationship status change. Moreover, the data were collected to better understand the characteristics of persons requiring child support, and to help develop and maintain programs designed to assist in obtaining child support. These data highlight alimony and child support arrangements made at the time of separation or divorce, amount of payments actually received, and value and type of any property settlement.The April supplement data were matched to March supplement data for households that were in the sample in both March and April 2008. In March 2008, there were 4,522 household members eligible, of which 1,431 required imputation of child support data. When matching the March 2008 and April 2008 data sets, there were 170 eligible people on the March file that did not match to people on the April file. Child support data for these 170 people were imputed. The remaining 1,261 imputed cases were due to nonresponse to the child support questions. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the preceding year, although other demographic data refer to the time at which the survey was administered.

Abstract

From 2002-2005 the Agincourt Integrated Family Survey project collected data in Limpopo Province, at the Agincourt Demographic Surveillance Site through the auspices of Philani Nutrition and Development Project. The work was funded by the National Institute on Aging under grant numbers R01 AG20275-01, P01 AG05842-14, and P30 AG024361. The project used integrated health and economic surveys in South Africa to investigate the links between health status and economic status. Our survey instruments collected data on a range of traditional and non-traditional measures of well-being including income and consumption, measures of health status (including mental health), morbidity, crime, social connectedness, intra-household relationships, and direct hedonic measures of well-being.

In 2004, the households who had been interviewed in 2002 were re-interviewed (if they were willing and if they could be found), for part 1 of the second wave. In 2005, the households who were interviewed in 2003 were re-interviewed (if they were willing and if they could be found), for part 2 of the second wave. For all of the studies, the methodology for conducting the surveys was the same. The questions varied some from year to year. The crosswalk (see table of contents) identifies these variations. In study years 2003, 2004, and 2005, detailed questions in the household questionnaire about the impact of the most recent death in the household were asked of the most knowledgeable household member.

Geographic coverage

The survey covered a rural sub-district in Mpumalanga Province, South Africa

Analysis unit

Households and individuals

Universe

The Agincourt Integrated Family Survey universe included all household residents, Woman aged 60 and above and men aged 65 and above in the household

Kind of data

Sample survey data

Sampling procedure

In January 2004, using Agincourt Health and Population Unit (AHPU) census information, the Agincourt Integrated Family Survey project team drew a stratified random sample of 475 households across all villages in the Agincourt Demographic Surveillance Site, with stratification on both citizenship (South African versus Mozambican) and on whether the household had lost a member to death in the period from June 1, 2002 to May 31, 2003. By "Mozambican household" in the sample design we mean that the nationality of the head of household is Mozambican.

Sampling deviation

The sample was designed to be 60 percent South African, and 40 percent Mozambican. In execution, slightly fewer South African households without a death were interviewed (187 instead of 190), and one extra South African household with a death was interviewed (96 instead of 95).

These discrepancies were the result of confusion over which households were considered to have a complete interview in cases where the head of household refused to be interviewed. The survey is composed of a household module, to be completed by a knowledgeable household member; an adult module, to be completed by each member aged 18 or older; and a child module, to be completed for each child aged 12 or younger. Some adult household members were migrants who were not in the field site to be interviewed (although the field team made a great effort to make appointments with the household to return at month-end, or at Easter, to interview returning migrants). In addition, some adult members refused to be interviewed. It was decided that if the household module was completed, and at least one adult was interviewed, the household had a complete interview. In the South African-Death Stratum, an extra household was interviewed because the household head came home for Easter, after the rest of the household had been interviewed, and refused to participate. The field team then interviewed a replacement household, but need not have as a decision had previously been made that if the head refused to participate, but did not stop other members from doing so, then that household's information would be used. However, if a returning head refused to let any members participate (even if they had already been interviewed),that household was not used in the analysis.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire: The most knowledgeable household member (khhm) was the initial person interviewed within the household. He or she would list all of the members of the household. This list of household members was then used as a guide for the entire interview process. The khhm first answered questions about the individual members of the household: age, gender, education, marital status, is that person?s partner in the household, is that person?s parent in the household. Additionally, the khhm was asked about the source and amount of income of each household member. Summary information was gathered from the khhm about the household members who had died and the household members who had moved. In study years starting in 2003, detailed questions were posed about the effect the most recent death had on the household. Detailed questions were asked of the khhm about the living conditions: access to toilet facilities and running water, a stove, a phone. Questions about household expenditure were asked

Adult Questionnaire: In 2002 there were two separate adult questionnaires. One questionnaire was for adults whose ages fell between 18 and 54; the second questionnaire was for adults 55 years old and up. In subsequent study years there was one questionnaire for adults 18 and older. Every adult from the household, who was available and willing to, answered these questions. Questions about age, marital status, number of living children, and number of children who have died were included. Detailed questions were asked about their sources of income and their expenditures. For older adults, there were questions about pensions and grants, for mothers there were questions about childcare grants. Individuals described the type of jobs they held over the years, how much money they earned and how they spent that money. Detailed health questions were posed; both physical and mental health issues were covered. Physical measurements were taken of the individuals interviewed: their height, weight, waist size; blood pressure and pulse.

Child Questionnaire: The parent or guardian of each child was questioned about the child. Questions included those on birth weight, history of breastfeeding and health of the child. With the parent's or guardian's permission the child?s height and weight were measured. Detailed information was recorded about the child?s immunization history.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.