The "https://addhealth.cpc.unc.edu/" Target="_blank">National Longitudinal Study of Adolescent to Adult Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32*. Add Health combines longitudinal survey data on respondents' social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The fifth wave of data collection is planned to begin in 2016.

Initiated in 1994 and supported by three program project grants from the "https://www.nichd.nih.gov/" Target="_blank">Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) with co-funding from 23 other federal agencies and foundations, Add Health is the largest, most comprehensive longitudinal survey of adolescents ever undertaken. Beginning with an in-school questionnaire administered to a nationally representative sample of students in grades 7-12, the study followed up with a series of in-home interviews conducted in 1995, 1996, 2001-02, and 2008. Other sources of data include questionnaires for parents, siblings, fellow students, and school administrators and interviews with romantic partners. Preexisting databases provide information about neighborhoods and communities.

Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health, and Waves I and II focus on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants have aged into adulthood, however, the scientific goals of the study have expanded and evolved. Wave III, conducted when respondents were between 18 and 26** years old, focuses on how adolescent experiences and behaviors are related to decisions, behavior, and health outcomes in the transition to adulthood. At Wave IV, respondents were ages 24-32* and assuming adult roles and responsibilities. Follow up at Wave IV has enabled researchers to study developmental and health trajectories across the life course of adolescence into adulthood using an integrative approach that combines the social, behavioral, and biomedical sciences in its research objectives, design, data collection, and analysis.

* 52 respondents were 33-34 years old at the time of the Wave IV interview.
** 24 respondents were 27-28 years old at the time of the Wave III interview.

Included here are weights to remove any differences between the composition of the sample and the estimated composition of the population. See the attached codebook for information regarding how these weights were calculated.

Calculation strategy for survey and population weighting of the data.

Stata module that implements Potter's (1990) weight distribution approach to trim extreme sampling weights. The basic idea is that the sampling weights are assumed to follow a beta distribution. The parameters of the distribution are estimated from the moments of the observed sampling weights and the resulting quantiles are used as cut-off points for extreme sampling weights. The process is repeated a specified number of times (10 by default) or until no sampling weights are more extreme than the specified quantiles.

Change in Three Population Estimates and Personal Network Size over the Original and MoS Estimator.

An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Asian Stoneware Jars" data publication.

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

R code containing a function that computes the Inverse Probability Sample Weight (IPSW) estimator, its variance and 95% Confidence Intervals (CI) for generalizing trial results to a target population.

The main table contains all data collected from each bottomfish received and processed over the course of the Federal Disaster Relief Program (FDRP)-funded Hawaiian Archipelago Bottomfish Sampling Program as well as fish collected on the Oscar Elton Sette, other research cruises including small boat operations, hapu'upu'puu received from the Laysan during a separate project, and any bottomfish...

Supplementary Material 1. Analysis Results.

The 1987 National Medical Expenditure Survey (NMES) Public Use Tape 6 contains data from a survey of two kinds of long-term care facilities: those for the mentally retarded, and nursing and personal care homes. The Facility Questionnaire was completed by administrators or designated staff of the participating facilities. The items include number of beds, type of ownership, facility certification, services routinely provided, staffing, average cost, sources of payment for residents, and levels of basic costs. Additional variables were collected on the facilities for the mentally retarded: education and habilitation services, licensure and accreditation, and sources of revenue in addition to direct client fees. Public Use Tape 6 differs from the data in the Facility Questionnaire file of Public Use Tape 2, National Medical Expenditure Survey, 1987: Institutional Population Component (ICPSR 9280) only in the provision of a revised sampling weight variable. The new sampling weight includes adjustment not only for different probabilities of a facility being selected, nonresponse, and stratification measures, but also for duplication in the sampling frame.

Original EPIC-1 data source and documented intermediate data manipulation. These files are provided in order to ensure a complete audit trail and documentation. These files include original source data, as well as files created in the process of cleaning and preparing the datasets found in section I of the dataverse (1. Pooled and Adjusted EPIC Data). These intermediary files contain documentation in any adjustment in assumptions, currency conversions, and data cleaning processes. Ordinarily, analysis would be done using the datasets in section I. Researchers would not find the need to use the files in this section unless for tracing the origin of the variables to the original source. “Adjustments for the EPIC-2 data is conducted with advice and input from data collection team (EPIC-1). The magnitude of these adjustments are documented in the table attached. These documented adjustments explained the lion’s share of the discrepancies, leaving only minor unaccounted differences in the data (Δ range 0% - 1.1%).” “In addition to using the sampling weights, any extrapolation to achieve nationwide cost estimates for Benin, Ghana, Zambia, and Honduras uses scale-up factor to take into account facilities that are outside of the sampling frame. For example, after taking into account the sampling weights, the total facility-level delivery cost in Benin sampling frame (343 facilities) is $2,094,031. To estimate the total facility-level delivery cost in the entire country of Benin (695 facilities), the sample-frame cost estimate is multiplied by 695/343. “Additional adjustments for the EPIC-2 analysis include the series of decisions for weighting, methods, and data sources. For EPIC-2 analyses, average costs per dose and DTP3 were calculated as total costs divided by total outputs, representing a funder’s perspective. We also report results as a simple average of the site-level cost per output. All estimates were adjusted for survey weighting. In particular, the analyses in EPIC-2 relied exclusively on information from the sample, whereas in some instance EPIC-1 teams were able to strategically leverage other available data sources.”

We propose an implementation of the particle filter in a quasi-static case in the example of Gaussian prior with independent and identically distributed prior states and observation errors. Weight collapse occurs in the particle filter when the number of model states and observations increases for a given ensemble size. In this example, we use a synthetic experiment to illustrate how weight collapse varies in the posterior distribution.

This code provides a basis for the implementation of importance sampling methods and can be easily adapted to other problems.

This dataset describes the sampling scheme used in the Baseline Study of Food for Peace Title II Development Food Assistance Program in Karamoja, Uganda. It has 34 columns and 4,766 rows. In fiscal year 2012, USAID's Office of Food for Peace (FFP) awarded funding to private voluntary organizations (PVOs) to design and implement a multi-year Title II development food assistance program in Uganda. The main purpose of the Title II program is to improve long-term food security of chronically food insecure population in the target regions. FFP contracted a firm, ICF International to conduct a baseline study in targeted areas of the country prior to the start of the new program. The purpose of the study was to assess the current status of key indicators, have a better understanding of prevailing conditions and perceptions of the population in the implementation areas, and serve as a point of comparison for future final evaluations. Results would also be used to further refine program targeting and, where possible, to understand the relationship between variables to inform program design. The study was conducted in 2013, while FFP expects to conduct final evaluations as close as possible to the end of the program five years later. The data asset is comprised of six datasets: 1) a description of all members of the households surveyed, 2) data on maternal health and sanitation practices, 3) data about the children in the household, 4) data describing the agricultural practices of the household, 5) data describing the food consumption of the household (broken into 4 smaller spreadsheets), and 6) and a description of the weights that should be applied during the analysis of the other datasets.

[2023-05-04 - Added WIC Infant and Toddler Feeding Practices Study-2 Data File Training Manual] The WIC Infant and Toddler Feeding Practices Study–2 (WIC ITFPS-2) (also known as the “Feeding My Baby Study”) is a national, longitudinal study that captures data on caregivers and their children who participated in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) around the time of the child’s birth. The study addresses a series of research questions regarding feeding practices, the effect of WIC services on those practices, and the health and nutrition outcomes of children on WIC. Additionally, the study assesses changes in behaviors and trends that may have occurred over the past 20 years by comparing findings to the WIC Infant Feeding Practices Study–1 (WIC IFPS-1), the last major study of the diets of infants on WIC. This longitudinal cohort study has generated a series of reports. These datasets include data from caregivers and their children during the prenatal period and during the children’s first four years of life (child ages 1 to 48 months). A full description of the study design and data collection methods can be found in Chapter 1 of the Second Year Report (https://www.fns.usda.gov/wic/wic-infant-and-toddler-feeding-practices-study-2-second-year-report). A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-ITFPS2-Year4Report-Appendix.pdf).
Processing methods and equipment used Data in this dataset were primarily collected via telephone interview with caregivers. Children’s length/height and weight data were objectively collected while at the WIC clinic or during visits with healthcare providers. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. Study date(s) and duration Data collection occurred between 2013 and 2018. Study spatial scale (size of replicates and spatial scale of study area) Respondents were primarily the caregivers of children who received WIC services around the time of the child’s birth. Level of true replication Unknown Sampling precision (within-replicate sampling or pseudoreplication) This dataset includes sampling weights that can be applied to produce national estimates. A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-ITFPS2-Year4Report-Appendix.pdf).
Level of subsampling (number and repeat or within-replicate sampling) A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-ITFPS2-Year4Report-Appendix.pdf).
Study design (before–after, control–impacts, time series, before–after-control–impacts) Longitudinal cohort study. Description of any data manipulation, modeling, or statistical analysis undertaken Each entry in the dataset contains caregiver-level responses to telephone interviews. Also available in the dataset are children’s length/height and weight data, which were objectively collected while at the WIC clinic or during visits with healthcare providers. In addition, the file contains derived variables used for analytic purposes. The file also includes weights created to produce national estimates. The dataset does not include any personally-identifiable information for the study children and/or for individuals who completed the telephone interviews. Description of any gaps in the data or other limiting factors Please refer to the Second Year Report (https://www.fns.usda.gov/wic/wic-infant-and-toddler-feeding-practices-study-2-second-year-report) for a detailed explanation of the study’s limitations. Outcome measurement methods and equipment used The majority of outcomes were measured via telephone interviews with children’s caregivers. Dietary intake was assessed using the USDA Automated Multiple Pass Method (https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/ampm-usda-automated-multiple-pass-method/). Children’s length/height and weight data were objectively collected while at the WIC clinic or during visits with healthcare providers. See file list for descriptions of each data file.

Between 1984 January - 2002 June, personnel from NMFS/PIFSC/FRMD/FMB/FMAP and Hawaii Department of Aquatic Resources (DAR) conducted port sampling at the United Fishing Agency (UFA) Fish Auction. They recorded the total landing at the UFA Fish Auction, with a frequency of six times a week during the earlier years to twice a week during the later years.

In 2000 January, DAR implemented a Dealer Data collection procedure that receives reports from the fish dealers that are more complete and covers more than just the auction. This Dealer Data takes the place of the UFA Sampling Data, and after a 2.5 year overlap, the collection of the UFA Sampling Data was discontinued in 2002 June. The DAR Dealer Data is archived and documented separately.

1: This value is the absolute value of the ratio of the estimated to the known (i.e. Column 2/Column 1) which is transformed with a logarithm (base 2). Successive columns (5, 7, 9, 11, 13, 15, 17) use the preceding estimation value.Recursive Back Estimation Process to Identify and Eliminate Poor Predictors Using the Original Estimator Without Weights.

These data are part of the Brine Disposal Program funded by NOAA in the US Gulf of Mexico, compiled by NOAA/CEAS and partially conducted by R. W. Hann of Texas A and M University. Grain size analyses conducted on 230 grabs by Texas A and M University were added to the historic NGDC Seafloor Sediment Grain Size Database from multiple cruises of the Lady Gloria conducted during October of 1982. Data include collecting institution, ship, cruise, sample id, latitude/longitude, date of collection, water depth, sampling device, method of analysis, sample weight, sampled interval, raw weight percentages of sediment, within a given phi range. Some samples also have percentages of total gravel, sand, silt, clay, and statistical measurements such as mean, median, skewness, kurtosis, and standard deviation of grain size. Additional data submitted for the Brine Disposal Program by Science Applications, Inc. (SAI) and collected during multiple cruises of the Texas Star in September of 1977, the Dixie Isle in March of 198, and the Gus III from October 1978-May of 1979 were not added to the database due to errors.

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

Abstract

The Social Indicator Sample Survey (SISS) was carried out in 2013 by the National Statistical Office of Mongolia in collaboration with UN Children’s Fund (UNICEF) and UN Population Fund (UNFPA), as part of the global Multiple Indicators Cluster Survey (MICS5) programme. UNICEF and UNFPA provided technical and financial support.

The survey, the largest of its kind ever conducted in Mongolia, included 15,500 households and combined the Multiple Indicators Cluster Survey (MICS), Reproductive Health Survey (RHS) and Demographic and Health Survey (DHS). This survey marked the introduction of tablets for large-scale data collection.

SISS 2013 collected data to compile indicators in health, education, development, protection, well-being and rights of children and women. In addition, data on reproductive health, family planning, knowledge and attitude towards HIV/AIDS, and sexual behaviour of Mongolian men and women was collected.

Geographic coverage

National

Analysis unit

• Households,
• Individuals

Universe

• Women age 15-49 living in a household
• Men age 15-54 living in a household
• Children under 5 living in a household
• Children age 5-14 living in a household

Kind of data

Sample survey data [ssd]

Sampling procedure

The Social Indicator Sample Survey is a household-based survey where households are defined as sampling units. Therefore, the households living in their administrative unit for 6 or more months or intended to live in for 6 or more months if not 6 months yet, are defined as sampling units in the survey concept.

The sample size is defined by having actual representation in urban-rural and regions (Western, Khangai, Central, Easternand Ulaanbaatar) when provides estimates of the survey result at the national level. 15,500 households were selected with probability proportional to size at the national level and it was decided to select sampling units using household unit weight for each region or unit weight of the region's households in the national rate.

Sample was selected in two stages. In the first stage, primary sampling units (baghs and khesegs) were selected with probability proportional to size. 25 households within each of these selected baghs and khesegs were selected using the systematic sampling method. The 2012 official household registration list was used as the sampling frame. Kheseg of khoroo's for Ulaanbaatar and baghs of soum's for aimags were defined as primary sampling units (PSUs). In total, 384 baghs of 236 soums of 21 aimags and 220 khesegs of 75 khoroos of 9 districts of Ulaanbaatar were covered by the survey and for each bagh and kheseg household lists were updated in May - July 2013. For reporting results, sample weights are used.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data was entered on electric database using the CSPro program. Procedures and standard programs developed under the global SISS programme and adapted to the SISS Mongolia 2013 questionnaire were used throughout. The data processing started from January 2014, where initial editing followed by logical editing were done. Developing syntax for main and additional tabulation started from February 2014 and completed by second half of April, 2014. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose. The UNFPA, UNICEF and global team of SISS reviewed and finalized all syntaxes of tabulation of the data processing. The preliminary results of the SISS were disseminated to the public and users on June 5, 2014. The national report was developed and included comments of the Steering Committee and Working Group of the survey and global team of the SISS.

This dataset contains small versions of model zoo datasets for our ICML 2024 paper "Towards Scalable and Versatile Weight Space Learning". These datasets are intended for testing and rapid pipeline evaluation of the code in the corresponding repository. For full model zoos, please see modelzoos.cc.