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

Survey on Equipment and Use of Information and Communication Technologies in Households: Internet users in the last 12 months who sent filled-in forms to the Public Administrations by demographic characteristics and sending method. National.

Demographic reports on TSP participant behavior and investment manager diversity are reported annually to Congress and available to the public via FRTIB’s Open Data Plan. Reports are in PDF format with included data tables.

The database FOLKNET contains information about the population in Sweden’s parishes, cities and municipalities according to the geographical division around 1990, every ten years during the period 1810–1990. The data has been collected by Christian Svärd, and the Demographic Data Base has digitized the information. The information has mainly been taken from Statistics Sweden’s historical publications. Additional data have been collected from the population forms of the database TABVERK. The database POPULATION is freely available from the home page of the Demographic Data Base.

This table includes information on business demography according to the European standard. Figures in this table are also submitted in this form to Eurostat. Information concerns the population of active enterprises, enterprise births and deaths, and the 1, 2, 3, 4 and 5 year survivors after birth, broken down by size class based on number of employees and by the National Classification of Economic Activity 2008 (NCEA 2008, based on NACE Rev 2.0). Data also includes persons employed and employees in active enterprises, births and deaths, as well as persons employed for surviving births at the start and end of the survival period.

Data available from: 2010

Status of the figures: The figures in this table are final for 2010 to 2021. The figures for 2022 are provisional. Only the data on Dissolved companies for 2022 will be adjusted.

Changes as of October 16, 2024: The provisional figures for 2022 have been added.

When will new figures be released? Figures on a new reporting year (T – 2) will be published in July of the current year T.

Release Date: 2024-08-08.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504866, Disclosure Review Board (DRB) approval number: 2021 NES-D approval number: CBDRB-FY24-0307; 2022 ABS approval number: CBDRB-FY23-0479)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female (50% / 50%). . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic (50% / 50%). Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority (50% / 50%). Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran (50% / 50%). Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown by the following legal form of organization (LFO) categories:. S-Corporations. C-Corporations. Individual proprietorships. Partnerships...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. For C-corporations, there is no tax form or business registry that clearly and unequivocally identifies all owners of this type of business. For this reason, the Census Bureau is unable to assign demographic characteristics for C-corporations. Data for C-corporations are included in the published tables but are not shown by the demographic characteristics of the firms....Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas. County...Data are also shown for the 3- and 4-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). Rail Transportation (NAICS 482). Postal Service (NAICS 491). Monetary Authorities-Central Bank (NAICS 521). Funds, Trusts, and Other Financial Vehicles (NAICS 525). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2021/AB2100NESD03.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2021/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not compara...

Survey on Equipment and Use of Information and Communication Technologies in Households: Internet users in the last year by demographic characteristics and participation in online bets and other forms of gambling in the last 12 months. National.

The Nonemployer Statistics by Demographics (NES-D): Company Summary estimates provide economic data classified by sex, ethnicity, race, and veteran status of nonemployer firms. The NES-D is not a survey; rather, it leverages existing administrative records to assign demographic characteristics to the universe of nonemployer businesses. The nonemployer universe is comprised of businesses with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries), and filing IRS tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series). Data for all firms are also presented. These estimates are produced by combining estimates for nonemployer firms from the Nonemployer Statistics by Demographics (NESD) and employer firms from the Annual Business Survey (ABS).

Release Date: 2024-02-08.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (2020 NES-D Project No. 7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0051)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female (50% / 50%). . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic (50% / 50%). Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority (50% / 50%). Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran (50% / 50%). Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown by the following legal form of organization (LFO) categories:. S-Corporations. C-Corporations. Individual proprietorships. Partnerships...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. For C-corporations, there is no tax form or business registry that clearly and unequivocally identifies all owners of this type of business. For this reason, the Census Bureau is unable to assign demographic characteristics for C-corporations. Data for C-corporations are included in the published tables but are not shown by the demographic characteristics of the firms....Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3- and 4-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). Rail Transportation (NAICS 482). Postal Service (NAICS 491). Monetary Authorities-Central Bank (NAICS 521). Funds, Trusts, and Other Financial Vehicles (NAICS 525). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2020/AB2000NESD03.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2020/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the...

Release Date: 2024-08-08.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504866, Disclosure Review Board (DRB) approval number: 2021 NES-D approval number: CBDRB-FY24-0307; 2022 ABS approval number: CBDRB-FY23-0479)...Key Table Information:.Data in this table combines estimates from the Annual Business Survey (employer firms) and the Nonemployer Statistics by Demographics (nonemployer firms)...Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Includes U.S. employer firms estimates of business ownership by sex, ethnicity, race, and veteran status from the 2022 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: For employer data only, the collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2022 ABS collection year produces statistics for the 2021 reference year. The "Year" column in the table is the reference year...Data Items and Other Identifying Records:.Data include estimates on:.Total number of employer and nonemployer firms. Total sales and receipts of employer and nonemployer firms (reported in $1,000 of dollars). Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars). Number of employer firms (firms with paid employees). Sales and receipts of employer firms (reported in $1,000s of dollars). Number of employees (during the March 12 pay period). Annual payroll of employer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female (50% / 50%). . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic (50% / 50%). Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority (50% / 50%). Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran (50% / 50%). Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown for the size of sales/receipts/revenue of the business:.Sales, value of shipments, or revenue size of firms:. Firms with sales/receipts of less than $5,000. Firms with sales/receipts of $5,000 to $9,999. Firms with sales/receipts of $10,000 to $24,999. Firms with sales/receipts of $25,000 to $49,999. Firms with sales/receipts of $50,000 to $99,999. Firms with sales/receipts of $100,000 to $249,999. Firms with sales/receipts of $250,000 to $499,999. Firms with sales/receipts of $500,000 to $999,999. Firms with sales/receipts of $1,000,000 or more. ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. Nonemployer data do not have standard error or relative standard error columns as these data are from the universe of nonemployer firms, not from a data sample....Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas. County...Data are also shown for the 3- and 4-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). ...

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 Nonemployer Statistics by Demographics (NES-D): Characteristics of Business Owners estimates provide information on selected economic and demographic characteristics of business owners tabulated by sex, ethnicity, race, and veteran status of an owner. Included in the universe are nonemployer businesses with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries), and filing IRS tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).

Abstract

The Thai Demographic and Health Survey (TDHS) was a nationally representative sample survey conducted from March through June 1988 to collect data on fertility, family planning, and child and maternal health. A total of 9,045 households and 6,775 ever-married women aged 15 to 49 were interviewed. Thai Demographic and Health Survey (TDHS) is carried out by the Institute of Population Studies (IPS) of Chulalongkorn University with the financial support from USAID through the Institute for Resource Development (IRD) at Westinghouse. The Institute of Population Studies was responsible for the overall implementation of the survey including sample design, preparation of field work, data collection and processing, and analysis of data. IPS has made available its personnel and office facilities to the project throughout the project duration. It serves as the headquarters for the survey.

The Thai Demographic and Health Survey (TDHS) was undertaken for the main purpose of providing data concerning fertility, family planning and maternal and child health to program managers and policy makers to facilitate their evaluation and planning of programs, and to population and health researchers to assist in their efforts to document and analyze the demographic and health situation. It is intended to provide information both on topics for which comparable data is not available from previous nationally representative surveys as well as to update trends with respect to a number of indicators available from previous surveys, in particular the Longitudinal Study of Social Economic and Demographic Change in 1969-73, the Survey of Fertility in Thailand in 1975, the National Survey of Family Planning Practices, Fertility and Mortality in 1979, and the three Contraceptive Prevalence Surveys in 1978/79, 1981 and 1984.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49

Universe

The population covered by the 1987 THADHS is defined as the universe of all women Ever-married women in the reproductive ages (i.e., women 15-49). This covered women in private households on the basis of a de facto coverage definition. Visitors and usual residents who were in the household the night before the first visit or before any subsequent visit during the few days the interviewing team was in the area were eligible. Excluded were the small number of married women aged under 15 and women not present in private households.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE AND ALLOCATION

The objective of the survey was to provide reliable estimates for major domains of the country. This consisted of two overlapping sets of reporting domains: (a) Five regions of the country namely Bangkok, north, northeast, central region (excluding Bangkok), and south; (b) Bangkok versus all provincial urban and all rural areas of the country. These requirements could be met by defining six non-overlapping sampling domains (Bangkok, provincial urban, and rural areas of each of the remaining 4 regions), and allocating approximately equal sample sizes to them. On the basis of past experience, available budget and overall reporting requirement, the target sample size was fixed at 7,000 interviews of ever-married women aged 15-49, expected to be found in around 9,000 households. Table A.I shows the actual number of households as well as eligible women selected and interviewed, by sampling domain (see Table i.I for reporting domains).

THE FRAME AND SAMPLE SELECTION

The frame for selecting the sample for urban areas, was provided by the National Statistical Office of Thailand and by the Ministry of the Interior for rural areas. It consisted of information on population size of various levels of administrative and census units, down to blocks in urban areas and villages in rural areas. The frame also included adequate maps and descriptions to identify these units. The extent to which the data were up-to-date as well as the quality of the data varied somewhat in different parts of the frame. Basically, the multi-stage stratified sampling design involved the following procedure. A specified number of sample areas were selected systematically from geographically/administratively ordered lists with probabilities proportional to the best available measure of size (PPS). Within selected areas (blocks or villages) new lists of households were prepared and systematic samples of households were selected. In principle, the sampling interval for the selection of households from lists was determined so as to yield a self weighting sample of households within each domain. However, in the absence of good measures of population size for all areas, these sampling intervals often required adjustments in the interest of controlling the size of the resulting sample. Variations in selection probabilities introduced due to such adjustment, where required, were compensated for by appropriate weighting of sample cases at the tabulation stage.

SAMPLE OUTCOME

The final sample of households was selected from lists prepared in the sample areas. The time interval between household listing and enumeration was generally very short, except to some extent in Bangkok where the listing itself took more time. In principle, the units of listing were the same as the ultimate units of sampling, namely households. However in a small proportion of cases, the former differed from the latter in several respects, identified at the stage of final enumeration: a) Some units listed actually contained more than one household each b) Some units were "blanks", that is, were demolished or not found to contain any eligible households at the time of enumeration. c) Some units were doubtful cases in as much as the household was reported as "not found" by the interviewer, but may in fact have existed.

Mode of data collection

Face-to-face

Research instrument

The DHS core questionnaires (Household, Eligible Women Respondent, and Community) were translated into Thai. A number of modifications were made largely to adapt them for use with an ever- married woman sample and to add a number of questions in areas that are of special interest to the Thai investigators but which were not covered in the standard core. Examples of such modifications included adding marital status and educational attainment to the household schedule, elaboration on questions in the individual questionnaire on educational attainment to take account of changes in the educational system during recent years, elaboration on questions on postnuptial residence, and adaptation of the questionnaire to take into account that only ever-married women are being interviewed rather than all women. More generally, attention was given to the wording of questions in Thai to ensure that the intent of the original English-language version was preserved.

a) Household questionnaire

The household questionnaire was used to list every member of the household who usually lives in the household and as well as visitors who slept in the household the night before the interviewer's visit. Information contained in the household questionnaire are age, sex, marital status, and education for each member (the last two items were asked only to members aged 13 and over). The head of the household or the spouse of the head of the household was the preferred respondent for the household questionnaire. However, if neither was available for interview, any adult member of the household was accepted as the respondent. Information from the household questionnaire was used to identify eligible women for the individual interview. To be eligible, a respondent had to be an ever-married woman aged 15-49 years old who had slept in the household 'the previous night'.

Prior evidence has indicated that when asked about current age, Thais are as likely to report age at next birthday as age at last birthday (the usual demographic definition of age). Since the birth date of each household number was not asked in the household questionnaire, it was not possible to calculate age at last birthday from the birthdate. Therefore a special procedure was followed to ensure that eligible women just under the higher boundary for eligible ages (i.e. 49 years old) were not mistakenly excluded from the eligible woman sample because of an overstated age. Ever-married women whose reported age was between 50-52 years old and who slept in the household the night before birthdate of the woman, it was discovered that these women (or any others being interviewed) were not actually within the eligible age range of 15-49, the interview was terminated and the case disqualified. This attempt recovered 69 eligible women who otherwise would have been missed because their reported age was over 50 years old or over.

b) Individual questionnaire

The questionnaire administered to eligible women was based on the DHS Model A Questionnaire for high contraceptive prevalence countries. The individual questionnaire has 8 sections: - Respondent's background - Reproduction - Contraception - Health and breastfeeding - Marriage - Fertility preference - Husband's background and woman's work - Heights and weights of children and mothers

The questionnaire was modified to suit the Thai context. As noted above, several questions were added to the standard DHS core questionnaire not only to meet the interest of IPS researchers hut also because of their relevance to the current demographic situation in Thailand. The supplemental questions are marked with an asterisk in the individual questionnaire. Questions concerning the following items were added in the individual questionnaire: - Did the respondent ever

The data is prepared using AmeriCorps members who began service on any day in fiscal year (FY) 2017. The members may have served 1 to 365 days during their term. Members who are in never served, disqualified, pre-service, or deferred statuses were excluded from this analysis.AmeriCorps VISTA and AmeriCorps NCCC race and ethnicity data come from the member application to serve. The code to extract the data between the two programs is the same.The ASN race and ethnicity data comes from the enrollment form. The enrollment form may exist multiple times if the member enrolled in more than one term. It is not uncommon for each enrollment form to have conflicting information about the member’s race and ethnicity. The member may have enrollment form data for terms served outside of the timeframe of the dataset. For example, if we are reporting on members who began service in FY17, then a member who also served in FY16 may have race and ethnicity information in the FY16 enrollment form and no race or ethnicity information or conflicting information in the FY17 enrollment form. In the case of conflicting information, this analysis assumes each instance of race designation is correct. If a member reports themselves as “Asian or Asian American” in one enrollment form and “White” in another enrollment form, then the analysis categorizes this person as someone who identifies with multiple race selections vs. one or the other. In the case of ethnicity, if a member indicates that they are not Hispanic or Latino/a in one form, but that they are in another, this analysis assumes the affirmative—and they will be categorized as Hispanic or Latino/a. Lastly, the totals include the total results from the query plus the difference between the query and the raw count of members who started service in that fiscal year. The members who did not have a record in the invite table and enrollment table were added to the non-response category.Senior Corps Figures come from the Annual Progress Report Supplement as of April 11, 2018.Percentages are calculated from totals of the subcategories, excluding the non-response categories.

In 2022, around seven in ten internet users in Denmark stated downloading official forms from public services websites. This figure has decreased by five percent since 2020.

The data is prepared using AmeriCorps members who began service on any day in fiscal year (FY) 2017. The members may have served 1 to 365 days during their term. Members who are in never served, disqualified, pre-service, or deferred statuses were excluded from this analysis. AmeriCorps VISTA and AmeriCorps NCCC race and ethnicity data come from the member application to serve. The code to extract the data between the two programs is the same. The ASN race and ethnicity data comes from the enrollment form. The enrollment form may exist multiple times if the member enrolled in more than one term. It is not uncommon for each enrollment form to have conflicting information about the member’s race and ethnicity. The member may have enrollment form data for terms served outside of the timeframe of the dataset. For example, if we are reporting on members who began service in FY17, then a member who also served in FY16 may have race and ethnicity information in the FY16 enrollment form and no race or ethnicity information or conflicting information in the FY17 enrollment form. In the case of conflicting information, this analysis assumes each instance of race designation is correct. If a member reports themselves as “Asian or Asian American” in one enrollment form and “White” in another enrollment form, then the analysis categorizes this person as someone who identifies with multiple race selections vs. one or the other. In the case of ethnicity, if a member indicates that they are not Hispanic or Latino/a in one form, but that they are in another, this analysis assumes the affirmative—and they will be categorized as Hispanic or Latino/a. Lastly, the totals include the total results from the query plus the difference between the query and the raw count of members who started service in that fiscal year. The members who did not have a record in the invite table and enrollment table were added to the non-response category. Senior Corps Figures come from the Annual Progress Report Supplement as of April 11, 2018. Percentages are calculated from totals of the subcategories, excluding the non-response categories.

Abstract

Vadu Rural Health Program, KEM Hospital Research Centre Pune has a rich tradition in health care and development being in the forefront of needs-based, issue-driven research over almost 35 years. During the decades of 1980 and 1990 the research at Vadu focused on mother and child with epidemiological and social science research exploring low birth weight, child survival, maternal mortality, safe abortion and domestic violence. The research portfolio has ever since expanded to include adult health and aging, non-communicable and communicable diseases and to clinical trials in recent years. It started with establishment of Health and Demographic Surveillance System at Vadu (HDSS Vadu) in August, 2002 that seeks to establish a quasi-experimental design setting to allow evaluation of impact of health interventions as well as monitor secular trends in diseases, risk factors and health behavior of humans.

The term "demographic surveillance" means to keep close track of the population dynamics. Vadu HDSS deals with keeping track of health issues and demographic changes in Vadu rural health program (VRHP) area. It is one of the most promising projects of national relevance that aims at establishing a quasi-experimental intervention research setting with the following objectives: 1) To create a longitudinal data base for efficient service delivery, future research, and linking all past micro-studies in Vadu area 2) Monitoring trends in public health problems 3) Keeping track of population dynamics 4) Evaluating intervention services

This dataset contains the events of all individuals ever resident during the study period (1 Jan. 2009 to 31 Dec. 2015).

Geographic coverage

Vadu HDSS falls in two administrative blocks: (1) Shirur and (2) Haweli of Pune district in Maharashtra in western India. It covers an area of approximately 232 square kilometers.

Analysis unit

Individual

Universe

Vadu HDSS covers as many as 50,000 households having 140,000 population spread across 22 villages.

Kind of data

Event history data

Frequency of data collection

Two rounds per year

Sampling procedure

Vadu area including 22 villages in two administrative blocks is the study area. This area was selected as this is primarily coverage area of Vadu Rural Health Program which is in function since more than four decade. Every individual household is included in HDSS. There is no sampling strategy employed as 100% population coverage in the area is expected.

Mode of data collection

Proxy Respondent [proxy]

Research instrument

Language of communication is in Marath or Hindi. The form labels are multilingual - in English and Marathi, but the data entered through the forms are in English only.

The following forms were used: - Field Worker Checklist Form - The checklist provides a guideline to ensure that all the households are covered during the round and the events occurred in each household are captured. - Enumeration Form: To capture the population details at the start of the HDSS or any addition of villages afterwards. - Pregnancy Form: To capture pregnancy details of women in the age group 15 to 49. - Birth Form: To capture the details of the birth events.
- Inmigration Form: To capture inward population movement from outside the HDSS area and also for movement within the HDSS area. - Outmigration Form: To capture outward population movement from inside the HDSS area and also for movement within the HDSS area. - Death Form: To capture death events.

Cleaning operations

Entered data undergo a data cleaning process. During the cleaning process all error data are either corrected in consultaiton with the data QC team or the respective forms are sent back to the field for re collection of correct data. Data editors have the access to the raw dataset for making necessary editing after corrected data are bought from the field.

For all individuals whose enumeration (ENU), Inmigration (IMG) or Birth (BTH) have occurred before the left censoring date (2009-01-01) and have not outmigrated (OMG) or not died (DTH) before the left censoring date (2009-01-01) are included in the dataset as Enumeration (ENU) with EventDate as the left censored date (2009-01-01). But the actual date of observation of the event (ENU, BTH, IMG) is retained in the dataset as observation date for these left censored ENU events. The individual is dropped from the dataset if their end event (OMG or DTH) is prior to the left censoring date (2009-01-01)

Response rate

On an average the response rate is 99.99% in all rounds over the years.

Sampling error estimates

Not Applicable

Data appraisal

Data is cleaned to an acceptable level against the standard data rules using Pentaho Data Integration Comminity Edition (PDI CE) tool. After the cleaning process, quality metrics were as follows:

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate IN021 MicroDataCleaned Starts 1 301112 301113 0. 2017-05-31 20:06
IN021 MicroDataCleaned Transitions 0 667010 667010 0. 2017-05-31 20:07
IN021 MicroDataCleaned Ends 301113 2017-05-31 20:07
IN021 MicroDataCleaned SexValues 29 666981 667010 0. 2017-05-31 20:07
IN021 MicroDataCleaned DoBValues 575 666435 667010 0. 2017-05-31 20:07

Note: Except lower under five mortality in 2012 and lower adult mortality among females in 2013, all other estimates are fairly within expected range. Data underwent additional review in terms of electronic data capture, data cleaning and management to look for reasons for lower under five mortality rates in 2013 and lower female adult mortality in 2013. The additional review returned marginally higher rates and this supplements the validity of collected data. Further field related review of 2012 and 2013 data are underway and any revisions to published data/figures will be shared at a later stage.

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

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

This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The units of geography used for the 2010 Census maps displayed here are the Census tracts. Census tracts generally have a population size between 1 - 200 and 8 - 000 people - with an optimum size of 4 - 000 people. When first delineated - census tracts were designed to be homogeneous with respect to population characteristics - economic status - and living conditions. Census tract boundaries generally follow visible and identifiable features. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances - a census tract may consist of noncontiguous areas. The data collected on the short form survey are general demographic characteristics such as age - race - ethnicity - household relationship - housing vacancy and tenure (owner/renter).Feature Service Link:http://geodata.md.gov/imap/rest/services/Demographics/MD_CensusData/FeatureServer/0 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Release Date: 2021-12-16.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY22-032)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded....Industry and Geography Coverage:.Data are shown for the total for all sectors (00) and the 2- and 3-digit NAICS levels for the U.S. and states. For the metro areas, data are shown for the total for all sectors (00) and the 2-digit NAICS level only. Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). Rail Transportation (NAICS 482). Postal Service (NAICS 491). Monetary Authorities-Central Bank (NAICS 521). Funds, Trusts, and Other Financial Vehicles (NAICS 525). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2018/AB1800NESD01.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2018/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the level of noise applied to the data:. G - Low noise: The cell value was changed by less than 2 percent by the application of noise.. H - Moderate noise: The cell value was changed by 2 percent or more but less than 5 percent by the application of noise.. J - High noise: The cell value was changed by 5 percent or more by the application of noise..For a complete list of all economic programs symbols, see the Symbols Glossary...Source:.U.S. Census Bureau, Nonemployer Statistics by Demographics, Annual Business Survey Program.For more information about the survey, please visit https://www.census.gov/programs-surveys/abs.html...Contact Information:.To contact the Annual Business Survey Program staff:.Em...