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

Open Science in (Higher) Education – data of the February 2017 survey

This data set contains:

• Full raw (anonymised) data set (completed responses) of Open Science in (Higher) Education February 2017 survey. Data are in xlsx and sav format.
• Survey questionnaires with variables and settings (German original and English translation) in pdf. The English questionnaire was not used in the February 2017 survey, but only serves as translation.
• Readme file (txt)

Survey structure

The survey includes 24 questions and its structure can be separated in five major themes: material used in courses (5), OER awareness, usage and development (6), collaborative tools used in courses (2), assessment and participation options (5), demographics (4). The last two questions include an open text questions about general issues on the topics and singular open education experiences, and a request on forwarding the respondent’s e-mail address for further questionings. The online survey was created with Limesurvey[1]. Several questions include filters, i.e. these questions were only shown if a participants did choose a specific answer beforehand ([n/a] in Excel file, [.] In SPSS).

Demographic questions

Demographic questions asked about the current position, the discipline, birth year and gender. The classification of research disciplines was adapted to general disciplines at German higher education institutions. As we wanted to have a broad classification, we summarised several disciplines and came up with the following list, including the option “other” for respondents who do not feel confident with the proposed classification:

• Natural Sciences
• Arts and Humanities or Social Sciences
• Economics
• Law
• Medicine
• Computer Sciences, Engineering, Technics
• Other

The current job position classification was also chosen according to common positions in Germany, including positions with a teaching responsibility at higher education institutions. Here, we also included the option “other” for respondents who do not feel confident with the proposed classification:

• Professor
• Special education teacher
• Academic/scientific assistant or research fellow (research and teaching)
• Academic staff (teaching)
• Student assistant
• Other

We chose to have a free text (numerical) for asking about a respondent’s year of birth because we did not want to pre-classify respondents’ age intervals. It leaves us options to have different analysis on answers and possible correlations to the respondents’ age. Asking about the country was left out as the survey was designed for academics in Germany.

Remark on OER question

Data from earlier surveys revealed that academics suffer confusion about the proper definition of OER^[2]. Some seem to understand OER as free resources, or only refer to open source software (Allen & Seaman, 2016, p. 11). Allen and Seaman (2016) decided to give a broad explanation of OER, avoiding details to not tempt the participant to claim “aware”. Thus, there is a danger of having a bias when giving an explanation. We decided not to give an explanation, but keep this question simple. We assume that either someone knows about OER or not. If they had not heard of the term before, they do not probably use OER (at least not consciously) or create them.

Data collection

The target group of the survey was academics at German institutions of higher education, mainly universities and universities of applied sciences. To reach them we sent the survey to diverse institutional-intern and extern mailing lists and via personal contacts. Included lists were discipline-based lists, lists deriving from higher education and higher education didactic communities as well as lists from open science and OER communities. Additionally, personal e-mails were sent to presidents and contact persons from those communities, and Twitter was used to spread the survey.

The survey was online from Feb 6^th to March 3^rd 2017, e-mails were mainly sent at the beginning and around mid-term.

Data clearance

We got 360 responses, whereof Limesurvey counted 208 completes and 152 incompletes. Two responses were marked as incomplete, but after checking them turned out to be complete, and we added them to the complete responses dataset. Thus, this data set includes 210 complete responses. From those 150 incomplete responses, 58 respondents did not answer 1st question, 40 respondents discontinued after 1st question. Data shows a constant decline in response answers, we did not detect any striking survey question with a high dropout rate. We deleted incomplete responses and they are not in this data set.

Due to data privacy reasons, we deleted seven variables automatically assigned by Limesurvey: submitdate, lastpage, startlanguage, startdate, datestamp, ipaddr, refurl. We also deleted answers to question N^o 24 (email address).

References

Allen, E., & Seaman, J. (2016). Opening the Textbook: Educational Resources in U.S. Higher Education, 2015-16.

First results of the survey are presented in the poster:

Heck, Tamara, Blümel, Ina, Heller, Lambert, Mazarakis, Athanasios, Peters, Isabella, Scherp, Ansgar, & Weisel, Luzian. (2017). Survey: Open Science in Higher Education. Zenodo. http://doi.org/10.5281/zenodo.400561

Contact:

Open Science in (Higher) Education working group, see http://www.leibniz-science20.de/forschung/projekte/laufende-projekte/open-science-in-higher-education/.

[1] https://www.limesurvey.org

[2] The survey question about the awareness of OER gave a broad explanation, avoiding details to not tempt the participant to claim “aware”.

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2007-2008 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2006. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey.

In the 2005-2006 wave, the NHANES includes over 100 datasets. Most have been combined into three datasets for convenience. Each starts with the Demographic dataset and includes datasets of a specific type.

1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 2005-2006 (The base of the Demographic dataset + all data from medical examinations).

2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 2005-2006 (The base of the Demographic dataset + all data from medical laboratories).

3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 2005-2006 (The base of the Demographic dataset + all data from questionnaires)

Not all files from the 2005-2006 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e., some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website at the CDC:

Examination: Dietary Interview (Individual Foods -- First Day)
Examination: Dietary Interview (Individual Foods -- Second Day)
Examination: Food Frequency Questionnaire -- DietCalc Output
Examination: Physical Activity Monitor
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Dietary Supplement Use -- Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications

Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.

Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website.

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.

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

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

Abstract

The Gallup Poll Social Series (GPSS) is a set of public opinion surveys designed to monitor U.S. adults' views on numerous social, economic, and political topics. The topics are arranged thematically across 12 surveys. Gallup administers these surveys during the same month every year and includes the survey's core trend questions in the same order each administration. Using this consistent standard allows for unprecedented analysis of changes in trend data that are not susceptible to question order bias and seasonal effects.

Introduced in 2001, the GPSS is the primary method Gallup uses to update several hundred long-term Gallup trend questions, some dating back to the 1930s. The series also includes many newer questions added to address contemporary issues as they emerge.

The dataset currently includes responses from up to and including 2025.

Methodology

Gallup conducts one GPSS survey per month, with each devoted to a different topic, as follows:

January: Mood of the Nation

February: World Affairs

March: Environment

April: Economy and Finance

May: Values and Beliefs

June: Minority Rights and Relations (discontinued after 2016)

July: Consumption Habits

August: Work and Education

September: Governance

October: Crime

November: Health

December: Lifestyle (conducted 2001-2008)

The core questions of the surveys differ each month, but several questions assessing the state of the nation are standard on all 12: presidential job approval, congressional job approval, satisfaction with the direction of the U.S., assessment of the U.S. job market, and an open-ended measurement of the nation's "most important problem." Additionally, Gallup includes extensive demographic questions on each survey, allowing for in-depth analysis of trends.

Interviews are conducted with U.S. adults aged 18 and older living in all 50 states and the District of Columbia using a dual-frame design, which includes both landline and cellphone numbers. Gallup samples landline and cellphone numbers using random-digit-dial methods. Gallup purchases samples for this study from Dynata. Gallup chooses landline respondents at random within each household based on which member had the next birthday. As of June 2023, each sample of national adults includes a minimum quota of 80% cellphone respondents and 20% landline respondents, with additional minimum quotas by time zone within region. Gallup conducts interviews in Spanish for respondents who are primarily Spanish-speaking.

Gallup interviews a minimum of 1,000 U.S. adults aged 18 and older for each GPSS survey. Samples for the June Minority Rights and Relations survey (conducted periodically between 2001 and 2021) were significantly larger because Gallup oversampled Black and Hispanic adults to allow for reliable estimates among these key subgroups.

Gallup weights samples to correct for unequal selection probability, nonresponse, and double coverage of landline and cellphone users in the two sampling frames. Gallup also weights its final samples to match the U.S. population according to gender, age, race, Hispanic ethnicity, education, region, population density, and phone status (cellphone only, landline only, both, and cellphone mostly).

Demographic weighting targets are based on the most recent Current Population Survey figures for the aged 18 and older U.S. population. Phone status targets are based on the most recent National Health Interview Survey. Population density targets are based on the most recent U.S. Census.

Usage

The year appended to each table name represents when the data was last updated. For example, January: Mood of the Nation - 2025** **has survey data collected up to and including 2025.

For more information about what survey questions were asked over time, see the Supporting Files.

Bulk Data Access

Data access is required to view this section.

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2007-2008 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2006. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey.

In the 2005-2006 wave, the NHANES includes over 100 datasets. Most have been combined into three datasets for convenience. Each starts with the Demographic dataset and includes datasets of a specific type.

1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 2005-2006 (The base of the Demographic dataset + all data from medical examinations).

2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 2005-2006 (The base of the Demographic dataset + all data from medical laboratories).

3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 2005-2006 (The base of the Demographic dataset + all data from questionnaires)

Not all files from the 2005-2006 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e., some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website at the CDC:

Examination: Dietary Interview (Individual Foods -- First Day)
Examination: Dietary Interview (Individual Foods -- Second Day)
Examination: Food Frequency Questionnaire -- DietCalc Output
Examination: Physical Activity Monitor
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Dietary Supplement Use -- Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications

Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.

Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website.

Abstract

The 2011 Bangladesh Demographic and Health Survey (BDHS) is the sixth DHS undertaken in Bangladesh, following those implemented in 1993-94, 1996-97, 1999-2000, 2004, and 2007. The main objectives of the 2011 BDHS are to: • Provide information to meet the monitoring and evaluation needs of health and family planning programs, and • Provide program managers and policy makers involved in these programs with the information they need to plan and implement future interventions.

The specific objectives of the 2011 BDHS were as follows: • To provide up-to-date data on demographic rates, particularly fertility and infant mortality rates, at the national and subnational level; • To analyze the direct and indirect factors that determine the level of and trends in fertility and mortality; • To measure the level of contraceptive use of currently married women; • To provide data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS; • To assess the nutritional status of children (under age 5), women, and men by means of anthropometric measurements (weight and height), and to assess infant and child feeding practices; • To provide data on maternal and child health, including antenatal care, assistance at delivery, breastfeeding, immunizations, and prevalence and treatment of diarrhea and other diseases among children under age 5; • To measure biomarkers, such as hemoglobin level for women and children, and blood pressure, and blood glucose for women and men 35 years and older; • To measure key education indicators, including school attendance ratios and primary school grade repetition and dropout rates; • To provide information on the causes of death among children under age 5; • To provide community-level data on accessibility and availability of health and family planning services; • To measure food security.

The 2011 BDHS was conducted under the authority of the National Institute of Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare. The survey was implemented by Mitra and Associates, a Bangladeshi research firm located in Dhaka. ICF International of Calverton, Maryland, USA, provided technical assistance to the project as part of its international Demographic and Health Surveys program (MEASURE DHS). Financial support was provided by the U.S. Agency for International Development (USAID).

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Universe

The 2011 BDHS covers the entire population residing in noninstitutional dwelling units in the country.

Kind of data

Sample survey data

Sampling procedure

Sample Design The sample for the 2011 BDHS is nationally representative and covers the entire population residing in noninstitutional dwelling units in the country. The survey used as a sampling frame the list of enumeration areas (EAs) prepared for the 2011 Population and Housing Census, provided by the Bangladesh Bureau of Statistics (BBS). The primary sampling unit (PSU) for the survey is an EA that was created to have an average of about 120 households.

Bangladesh has seven administrative divisions: Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet. Each division is subdivided into zilas, and each zila into upazilas. Each urban area in an upazila is divided into wards, and into mohallas within a ward. A rural area in the upazila is divided into union parishads (UP) and mouzas within a UP. These divisions allow the country as a whole to be easily separated into rural and urban areas.

The survey is based on a two-stage stratified sample of households. In the first stage, 600 EAs were selected with probability proportional to the EA size, with 207 clusters in urban areas and 393 in 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. In the second stage of sampling, a systematic sample of 30 households on average was selected per EA to provide statistically reliable estimates of key demographic and health variables for the country as a whole, for urban and rural areas separately, and for each of the seven divisions. With this design, the survey selected 18,000 residential households, which were expected to result in completed interviews with about 18,000 ever-married women. In addition, in a subsample of one-third of the households, all evermarried men age 15-54 were selected and interviewed for the male survey. In this subsample, a group of eligible members were selected to participate in testing of the biomarker component, including blood pressure measurements, anemia, blood glucose testing, and height and weight measurements.

Note: See Appendix A (in final survey report) for the details of the sample design.

Sampling deviation

The 2007 BDHS sampled all ever-married women age 10-49. The number of eligible women age 10-49 was 11,234, of whom 11,051 were interviewed for a response rate of 98.4 percent. However, there were very few ever-married women age 10-14 (55 unweighted cases or less than one percent). These women have been removed from the data set and weights recalculated for the 15-49 age group. The tables in the survey report discuss only women age 15-49.

Mode of data collection

Face-to-face

Research instrument

The 2011 BDHS used five types of questionnaires: a Household Questionnaire, a Woman’s Questionnaire, a Man’s Questionnaire, a Community Questionnaire, and two Verbal Autopsy Questionnaires to collect data on causes of death among children under age 5. The contents of the household and individual questionnaires were based on the MEASURE DHS model questionnaires. These model questionnaires were adapted for use in Bangladesh during a series of meetings with a Technical Working Group (TWG) that consisted of representatives from NIPORT, Mitra and Associates, International Centre for Diarrheal Diseases and Control, Bangladesh (ICDDR,B), USAID/Bangladesh, and MEASURE DHS. Draft questionnaires were then circulated to other interested groups and were reviewed by the 2011 BDHS Technical Review Committee. The questionnaires were developed in English and then translated and printed into Bangla.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, information was collected about the dwelling unit, such as the source of water, type of toilet facilities, materials used to construct the floors and walls, and ownership of various consumer goods. The Household Questionnaire was also used to record for eligible individuals: • Height and weight measurements • Anemia test results • Measurements of blood pressure and blood glucose

The Woman’s Questionnaire was used to collect information from ever-married women age 12-49. Women were asked questions on the following topics: • Background characteristics (e.g., age, education, religion, and media exposure) • Reproductive history • Use and source of family planning methods • Antenatal, delivery, postnatal, and newborn care • Breastfeeding and infant feeding practices • Child immunizations and childhood illnesses • Marriage • Fertility preferences • Husband’s background and respondent’s work • Awareness of AIDS and other sexually transmitted infections • Food security

The Man’s Questionnaire was used to collect information from ever-married men age 15-54. Men were asked questions on the following topics: • Background characteristics (including respondent’s work) • Marriage • Fertility preferences • Participation in reproductive health care • Awareness of AIDS and other sexually transmitted infections

The Community Questionnaire was administered in each selected cluster during the household listing operation. Data were collected by administering the Community Questionnaire to a group of four to six community leaders who were knowledgeable about socioeconomic conditions and the availability of health and family planning services/facilities, in or near the sample area (cluster). Community leaders included such persons as government officials, social workers, teachers, religious leaders, traditional healers, and health care providers.

The Community Questionnaire collected information about the existence of development organizations in the community and the availability and accessibility of health services and other facilities. During the household listing operation, the geographic coordinates and altitude of each cluster were also recorded. The information obtained in these questionnaires was also used to verify information gathered in the Woman’s and Man’s Questionnaires on the types of facilities accessed and health services personnel seen.

The Verbal Autopsy Questionnaires were developed based on the work done by an expert group led by the WHO, consisting of researchers, data users, and other stakeholders under the sponsorship of the Health Metrics Network (HMN). The verbal autopsy tools are intended to serve the various needs of the users of mortality information. Two questionnaires were used to collect information related to the causes of death among young children; the first questionnaire collected data on neonatal deaths (deaths at 0-28 days), and the

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, Round 7 (2016-2018) 34 countries, and Round 8 (2019-2021). The survey covered 39 countries in Round 9 (2021-2023).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens of Mali who are 18 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

Mali - Sample size: 1,200 - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and urban-rural location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual - Weighting: Weighted to account for individual selection probabilities

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 9 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Response rate was 98%.

Sampling error estimates

The sample size yields country-level results with a margin of error of +/-3 percentage points at a 95% confidence level.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer Sampling Procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Benin - Sample size: 1,200 - Sampling frame: 2013 sampling frame updated from the General Population and Housing Census (RGPH 4) - Sample design: Nationally representative, random, clustered, stratified, multistage area, probability sampling - Stratification: Region, urban-rural distributio - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability proportional to population size (PPPS) - Cluster size: 8 households per PSU - Household selection: Random choice of the starting point, followed by the sampling interval using an interval of 5/10 households - Respondent selection: Gender quota to be achieved by alternating interviews between men and women; potential respondents (i.e. household members) of the appropriate gender are listed, then the computer randomly selects the individual

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Response rate was 80%.

Responses from the 2021 open participation (non-probability) 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 open participation survey data were weighted, meaning that the demographic profile of respondents was compared to the demographic profile of adults in Bloomington from US Census data. Statistical adjustments were made to bring the respondent profile into balance with the population profile. This means that some records were given more "weight" and some records were given less weight. The weights that were applied are found in the field "wt". If you do not apply these weights, you will not obtain the same results as can be found in the report delivered to the Bloomington. The easiest way to replicate these results is likely to create pivot tables, and use the sum of the "wt" field rather than a count of responses.

Abstract

The Survey Assessment of Vietnamese Youth (SAVY) undertaken in late 2003 was a collaboration of the Ministry of Health, General Statistics Office with technical and financial support from the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF).

This is the first nationwide baseline survey of youth ever undertaken in Viet Nam. It mainly aims to collect data on various aspects of youth life in order to inform policy and programmes in the adolescent and youth health and development area.

SAVY reveals a positive picture of Vietnamese youth as they face both challenges and opportunities in a changing economic and social environment. Compared with young people in other Asian countries, Vietnamese youth display relatively less risky behaviour, are supported by protective factors and are optimistic and eager to build a prosperous country. However, this survey does reveal that some young people will encounter considerable challenges in their transition to adulthood, unless provided with support. It is important that parents, the community and the government, with the support of international agencies and young people, work together to ensure the healthy development of young people in Viet Nam.

The survey involved 7,584 youth aged 14-25 years from 42 provinces across the country, from the smallest rural hamlet to the largest cities. Using a household sample, youth were invited to a central location to complete both a face-to-face interview and a self-administered anonymous survey which contained sensitive questions young people could answer in private. What results is the most extensive understanding of the social life, attitudes and aspirations of young Vietnamese people today.

Survey Objectives - Provide information that can best inform future initiatives to promote the healthy development of youth across the country; - Inform policy and program development in the Adolescent and Youth Health area in the immediate future; and - Provide baseline data about Vietnamese youth to identify trends and patterns in the coming years.

Survey Content The questionnaire was designed through a very dynamic process, where experience from previous surveys was examined and opinion of young people ware actively solicited to ensure quality and relevance. The specific information collected through the questionnaire includes: Personal demographics Schooling, education Vocational training, Work and employment Puberty: knowledge and behaviors about reproductive health Dating and friendships HIV/AIDS Injury, illness and physical health Attitudes, perceptions and behaviors Social factors and emotional wellbeing Mass media Future aspirations

Survey Implementation SAVY is a collaborative effort between many agencies and young people. It is the result of extensive investment and parnership building between the Vietnamese Government through the Ministry of Health, the General Statistics Office, and United Nations agencies, notably The World Health Organisation and the United Nations Children's Fund. Several other organizations, from a variety of sectors, also contributed to the endeavor, notably the Ministry of Education and Training (MoET), the Central Youth Union (YU) and the Vietnam Women's Union (VWU). In order to ensure that the survey was methodologically sound, the East- West Centrer (Honolulu, Hawaii) provided intensive technical assisstance.

Survey Results Results from the surveys, including national reports, and micro level datasets. The dataset was formatted by *.sav (SPSS) and *.dta (STATA) More information and electronic files of SAVY, visit : http://www.moh.gov.vn/SKSS/Savy_htm/savy.htm

Geographic coverage

National

Analysis unit

Youth aged 14-25 years

Universe

The survey covered all youths aged 14-25 years resident in the household. The SAVY sample did not include Vietnamese youth not living with their families nor those living in military barracks, social protection centers, dormitories, re-education centers and drug treatment centers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The SAVY sample is a national representative sample of youth (persons ages 14-25 years) living in households across the eight economic regions of Viet Nam. THe sample was drawn from the sub-sample of 45,000 households in the 2002 Viet Nam Living Standards Survey (VLSS 2002), within a multi-staged and stratified design. The youth in the SAVY sample design are sufficient to represent the nation as a whole, as well as the urban and rural separely. The largest cities (Hanoi and Ho Chi Minh) were over sampled in order to provide for increased statistical power in that segment of the total population of youth.

Forty-two out of 61 provinces were selected for the SAVY sample, using the probability proportional to size (PPS) method to maintain representativeness . At the next stage of sampling, enumeration areas (EAs) in each province were selected. In those EAs sampled, all youth aged 14 through 25 were identified (i.e, those born between 1978 and 1989) males and females, married and non married from the 20 households that had been selected for the VLSS2002. The youth cohort represents all youth, but not those living in special arrangements, such as barracks, re-education centers, social protection centers, factories and dormitories.

The 61 provinces in the VLSS 2002 sample included 2.250 EAS, and the 42 provinces selected for SAVY included 1643 EAs. From these, a total of 446 EAs were selected for the SAVY sample. These EAs contained 8920 households corresponding to a population of 40,140 (about 4.5 persons per household). Since youth aged 14-25 account for 24.5% of the total population (the figure in the 1999 census), the anticipated number of youth in the SAVY sample was approximately 9,835. If the mobilization rate (percentage of eligible youth actually interviewed) was 90% then the number of youth interviewed woul be estimated to be about 8,850. In the actual SAVY field experiece, the mobilization rate was 85% and the number of completed interviews was 7,584.

The sample is therefore representative, and provides sufficient cases for analysis at the national level within urban and rural sectors at the national level, by gender at the nation level, and for each of the regions. Further detail on the sampling methodology is provided in the Appendix of the Final Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed through a very dynamic process, where experience from previous surveys was examined and opinions of young people were actively solicited to ensure quality and relevance. This process also helped to define the methodology and implications for fieldwork planning.

A number of stakeholders’ agencies, including research institutes, were involved in the development of the questionnaire. This process ensured broad participation and ownership of the questionnaire and the survey.

The questionnaire design took place in two stages. In the first stage, experienced researchers, and others interested in the survey as stakeholders, were convened to a workshop by the MoH. Potential topics, and the possible phrasing of questions using the questionnaire bank from previous studies in the region as reference, were fully discussed. Since some of the topics were deemed to be more sensitive than others, it was recommended that the questionnaire should be organized into two parts, one for an interview and the other for self-completion. On the basis of that workshop, a draft questionnaire was created for review by the workshop members and numerous others in stakeholder agencies, as well as by young people through a series of consultations.

Eight focus group discussions were conducted in Hanoi and HCMC, with around 60 young people of different ages in the 14-25 range who were either married or unmarried and either attending or not attending school. Participants gave detailed feedback about the terminology, the ways in which questions were posed and the sequencing of the questions, as well as which specific questions or issues they would prefer to respond to on their own, rather than with an interviewer. This process resulted in the rephrasing of a number of questions and changes to the self-completed section.

Preliminary training was conducted for field-testing of the questionnaire. Participants came from the GSO Office in Tuyen Quang, Hue and HCMC, representing the north, south and central regions of Viet Nam. A group of 50 young males and females, either married or unmarried and either attending or not attending school, participated in the interviewers’ practice session. In the debriefing discussions, these young people expressed their feelings about the interviews, the questions asked, what they liked and did not like about the process, seating arrangements, ideas of what topics/issues they thought might still be missing in the draft questionnaire, and what they thought would be needed to make good interviewers. Field testing with around 180 young people from six communes in these three provinces then took place.

The second stage involved further vetting of questionnaire sections and was coordinated by the GSO. The review meeting following the field trips recommended the need for another field testing exercise, particularly because little experience had been gained from testing with urban young people and interviewing ethnic minority young people through interpreters. Following the second round of field-testing in Hanoi and Yen Bai, the feedback was incorporated to finalise the questionnaire for the interviewers training. At the training, further revision and refinement of

Social Influence on Shopping

Social Survey Data from 300,000 Millennials and Gen Z Members

By Adam Halper [source]

About this dataset

This dataset offers a comprehensive look into the shopping habits of millennials and Gen Z members, including valuable insights about how their choices are influenced by social media. By exploring the responses given to survey questions related to this topic, we can gain an understanding of how these generations' interests, beliefs and desires shape their decisions when it comes to retail experiences. With 150 million survey responses from our 300,000+ millennial and Gen Z participants, we can uncover powerful insights that could help influencers, businesses and marketers more accurately target this demographic. Our data includes important information such as questions asked during the survey, segment types targeted by those questions and corresponding answers gathered with detailed counts/percentages - making this dataset incredibly useful for anyone wanting an in-depth understanding of what drives the purchasing behavior of today's youth

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

The first step in using this dataset is to take a look at each column: Question, Segment Type, Segment Description, Answer, Count & Percentage. The Question column will provide background on what exactly each survey question was asking - allowing you to get an overall view of what kind of topics were being surveyed in relation to millennials' shopping habits & social media influence. You will then be able to follow up with analysis based on the respective Segment Types & Descriptions given (such as income levels), which leads us into analyzing answers from both Count & Percentage columns combined - providing absolute numbers vs relative ones for further analysis (such as percentages).

Afterwards you'll need an advanced data analysis program such as SPSS or R-Studio - depending on your technical ability - though all most basic spreadsheet programs should suffice, excluding Matlab supported ones due its excessive complexity for something simple like this.. After selecting your preferred program inputting our file with all 150 million survey responses may take some time based on your computers processing capabilities but once loaded you'll be ready for endless possibilities! Now it's time get running with pulling out key insights you require utilizing various different tools found within these platforms whether it be linear regression or guided ANOVA testing which ever technique fits best should help lead navigate through uncovering deeper meaning in your ultra specific question!

As a final precaution while diving through waters filled surprises also keep note any adjustments needed potentially due overfitting or multicollinearity otherwise could cause major issues skew end results unfit requiring start whole process anew! Good luck delving deep discovering millennial behavior related digital world!

Research Ideas

• Identifying which type of segment is most responsive to engaging shopping experiences, such as influencer marketing, social media discounts and campaigns, etc.
• Analyzing the answers given to survey questions in order to understand millennial and Gen Z's opinion about social influence on their shopping habits - what do they view positively or negatively?
• Using the survey responses to uncover any interesting trends or correlations between different segments - is there a particular demographic that values or uses certain types of social influence on their shopping habits more than others?

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original.

Columns

File: WhatsgoodlyData-6.csv | Column name | Description ...

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, Round 7 (2016-2018) 34 countries, and Round 8 (2019-2021). The survey covered 39 countries in Round 9 (2021-2023).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens of Eswatini who are 18 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

Eswatini - Sample size: 1,200 - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region and urban-rural location - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual - Weighting: Weighted to account for individual selection probabilities - Sampling frame: Eswatini Central Statistics Office 2017 Population Census

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 9 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Response rate was 87%.

Sampling error estimates

The sample size yields country-level results with a margin of error of +/-3 percentage points at a 95% confidence level.

Abstract

The primary objective of the 2018 ZDHS was to provide up-to-date estimates of basic demographic and health indicators. Specifically, the ZDHS collected information on: - Fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; and gender, nutrition, and awareness regarding HIV/AIDS and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) - Ownership and use of mosquito nets as part of the national malaria eradication programmes - Health-related matters such as breastfeeding, maternal and childcare (antenatal, delivery, and postnatal), children’s immunisations, and childhood diseases - Anaemia prevalence among women age 15-49 and children age 6-59 months - Nutritional status of children under age 5 (via weight and height measurements) - HIV prevalence among men age 15-59 and women age 15-49 and behavioural risk factors related to HIV - Assessment of situation regarding violence against women

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 age 15-49, all men age 15-59, and all children age 0-5 years who are usual members of the selected households or who spent the night before the survey in the selected households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2018 ZDHS is the Census of Population and Housing (CPH) of the Republic of Zambia, conducted in 2010 by ZamStats. Zambia is divided into 10 provinces. Each province is subdivided into districts, each district into constituencies, and each constituency into wards. In addition to these administrative units, during the 2010 CPH each ward was divided into convenient areas called census supervisory areas (CSAs), and in turn each CSA was divided into enumeration areas (EAs). An enumeration area is a geographical area assigned to an enumerator for the purpose of conducting a census count; according to the Zambian census frame, each EA consists of an average of 110 households.

The current version of the EA frame for the 2010 CPH was updated to accommodate some changes in districts and constituencies that occurred between 2010 and 2017. The list of EAs incorporates census information on households and population counts. Each EA has a cartographic map delineating its boundaries, with identification information and a measure of size, which is the number of residential households enumerated in the 2010 CPH. This list of EAs was used as the sampling frame for the 2018 ZDHS.

The 2018 ZDHS followed a stratified two-stage sample design. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were selected with a probability proportional to their size within each sampling stratum. A total of 545 clusters were selected.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters. During the listing, an average of 133 households were found in each cluster, from which a fixed number of 25 households were selected through an equal probability systematic selection process, to obtain a total sample size of 13,625 households. Results from this sample are representative at the national, urban and rural, and provincial levels.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the 2018 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Zambia. Input on questionnaire content was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international cooperating partners. After all questionnaires were finalised in English, they were translated into seven local languages: Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

Cleaning operations

All electronic data files were transferred via a secure internet file streaming system to the ZamStats central office in Lusaka, 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. The data were processed by two IT specialists and one secondary editor who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in July 2018 and completed in March 2019.

Response rate

Of the 13,595 households in the sample, 12,943 were occupied. Of these occupied households, 12,831 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 14,189 women age 15-49 were identified as eligible for individual interviews; 13,683 women were interviewed, yielding a response rate of 96% (the same rate achieved in the 2013-14 survey). A total of 13,251 men were eligible for individual interviews; 12,132 of these men were interviewed, producing a response rate of 92% (a 1 percentage point increase from the previous survey).

Of the households successfully interviewed, 12,505 were interviewed in 2018 and 326 in 2019. As the large majority of households were interviewed in 2018 and the year for reference indicators is 2018.

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 2018 Zambia Demographic and Health Survey (ZDHS) 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 2018 ZDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2018 ZDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Completeness of information on siblings - Sibship size and sex ratio of siblings - Height and weight data completeness and quality for children - Number of enumeration areas completed by month, according to province, Zambia DHS 2018

Note: Data quality tables are presented in APPENDIX C of the report.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens aged 18 years and above excluding those living in institutionalized buildings.

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Gabon - Sample size: 1,200 - Sampling Frame: Recensement Général de la Population et des Logements (RGPL) de 2013 réalisée par la Direction Générale de la Statistique et des Etudes Economiques - Sample design: Representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Province, Department, and urban-rural location - Stages: Primary sampling unit (PSU), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota to be achieved by alternating interviews between men and women; potential respondents (i.e. household members) of the appropriate gender are listed, then the computer chooses the individual random

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Outcome rates: - Contact rate: 99% - Cooperation rate: 92% - Refusal rate: 3% - Response rate: 91%

Sampling error estimates

+/- 3% at 95% confidence level

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

Citizens of Mozambique who are 18 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999, the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements designed to meet current and emerging concerns. The sample for the survey is selected to represent the U.S. population of all ages. Many of the NHANES 2001-2002 questions also were asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups.

In the 2001-2002 wave, the NHANES includes more than 100 datasets. Most have been combined into three datasets for convenience. Each starts with the demographic dataset and includes datasets of a specific type.

1. National Health and Nutrition Examination Survey (NHANES), Demographic & Examination Data, 2001-2002 (The base of the Demographic dataset + all data from medical examinations).

2. National Health and Nutrition Examination Survey (NHANES), Demographic & Laboratory Data, 2001-2002 (The base of the Demographic dataset + all data from medical laboratories).

3. National Health and Nutrition Examination Survey (NHANES), Demographic & Questionnaire Data, 2001-2002 (The base of the Demographic dataset + all data from questionnaires)

Not all files from the 2001-2002 wave are included. This is for two reasons, both of which related to the merging variable (SEQN). For a subset of the files, SEQN is not a unique identifier for cases (i.e. some respondents have multiple cases) or SEQN is not in the file at all. The following datasets from this wave of the NHANES are not included in these three files and can be found individually from the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website at the CDC:

Examination: Dietary Interview (Individual Foods File)
Examination: Dual Energy X-ray Absorptiometry (DXX)
Examination: Dual Energy X-ray Absorptiometry (DXX)
Questionnaire: Analgesics Pain Relievers
Questionnaire: Dietary Supplement Use -- Ingredient Information
Questionnaire: Dietary Supplement Use -- Supplement Blend
Questionnaire: Dietary Supplement Use -- Supplement Information
Questionnaire: Drug Information
Questionnaire: Dietary Supplement Use -- Participants Use of Supplement
Questionnaire: Physical Activity Individual Activity File
Questionnaire: Prescription Medications

Variable SEQN is included for merging files within the waves. All data files should be sorted by SEQN.

Additional details of the design and content of each survey are available at the "https://www.cdc.gov/nchs/nhanes/index.html" Target="_blank">NHANES website.

Context

A group of Graduate researchers from Rider University in Lawrenceville, NJ were tasked with formulating a survey with 30 response questions to track social attitudes toward not having Children. The convenience method was used to sample the data

Content

The dataset contains two files :

(I) ChildlessnessNJ.csv: This is the main file containing demographic information of respondents and responses to survey questions on a scale of 1 to 5. The responses recorded by respondents can be interpreted according to the following scale:

(1 :Strongly Disagree that the particular question is an impacting factor on an individuals decision not to have children. 2: Disagree that the particular question is an impacting factor on an individuals decision not to have children. 3: Neutral. 4: Agree that the particular question is an impacting factor on an individuals decision not to have children. 5: Strongly Agree that the particular question is an impacting factor on an individuals decision not to have children.)

Please note that the above scale is reversed for Q12

(II) ChildlesnessQuestions.csv: As the survey questions are codified in the main file from Q1 through Q30, a separate file has been included bearing the following information:

*Question Code:*Indicates the column name of the survey questions in the main file(numbered Q1 to Q30) Full Question: This represents the full form of the asked question indicated by the Question Code. Construct Name: The Survey Response Questions can grouped/categorized into Construct groups or Question Groups to indicate the topic of the Survey Question. (Possible values are Financial, Choice, Outside Influences and Health)

Acknowledgements

All Kudos go to the graduate team at Rider University that conducted the survey and digitized the data. For more information about the dataset, email Bhavna at rajbh@rider.edu

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