The questions list for questionnaire – Demographics and basic work characteristics of survey respondents

Abstract

The Tanzania Demographic and Health Survey (TDHS) is part of the worldwide Demographic and Health Surveys (DHS) programme, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 1999 TRCHS was to collect data at the national level (with breakdowns by urban-rural and Mainland-Zanzibar residence wherever warranted) on fertility levels and preferences, family planning use, maternal and child health, breastfeeding practices, nutritional status of young children, childhood mortality levels, knowledge and behaviour regarding HIV/AIDS, and the availability of specific health services within the community.1 Related objectives were to produce these results in a timely manner and to ensure that the data were disseminated to a wide audience of potential users in governmental and nongovernmental organisations within and outside Tanzania. The ultimate intent is to use the information to evaluate current programmes and to design new strategies for improving health and family planning services for the people of Tanzania.

Geographic coverage

National. The sample was designed to provide estimates for the whole country, for urban and rural areas separately, and for Zanzibar and, in some cases, Unguja and Pemba separately.

Analysis unit

Households, individuals

Universe

Men and women 15-49, children under 5

Kind of data

Sample survey data

Sampling procedure

The TRCHS used a three-stage sample design. Overall, 176 census enumeration areas were selected (146 on the Mainland and 30 in Zanzibar) with probability proportional to size on an approximately self-weighting basis on the Mainland, but with oversampling of urban areas and Zanzibar. To reduce costs and maximise the ability to identify trends over time, these enumeration areas were selected from the 357 sample points that were used in the 1996 TDHS, which in turn were selected from the 1988 census frame of enumeration in a two-stage process (first wards/branches and then enumeration areas within wards/branches). Before the data collection, fieldwork teams visited the selected enumeration areas to list all the households. From these lists, households were selected to be interviewed. The sample was designed to provide estimates for the whole country, for urban and rural areas separately, and for Zanzibar and, in some cases, Unguja and Pemba separately. The health facilities component of the TRCHS involved visiting hospitals, health centres, and pharmacies located in areas around the households interviewed. In this way, the data from the two components can be linked and a richer dataset produced.

See detailed sample implementation in the APPENDIX A of the final report.

Mode of data collection

Face-to-face

Research instrument

The household survey component of the TRCHS involved three questionnaires: 1) a Household Questionnaire, 2) a Women’s Questionnaire for all individual women age 15-49 in the selected households, and 3) a Men’s Questionnaire for all men age 15-59.

The health facilities survey involved six questionnaires: 1) a Community Questionnaire administered to men and women in each selected enumeration area; 2) a Facility Questionnaire; 3) a Facility Inventory; 4) a Service Provider Questionnaire; 5) a Pharmacy Inventory Questionnaire; and 6) a questionnaire for the District Medical Officers.

All these instruments were based on model questionnaires developed for the MEASURE programme, as well as on the questionnaires used in the 1991-92 TDHS, the 1994 TKAP, and the 1996 TDHS. These model questionnaires were adapted for use in Tanzania during meetings with representatives from the Ministry of Health, the University of Dar es Salaam, the Tanzania Food and Nutrition Centre, USAID/Tanzania, UNICEF/Tanzania, UNFPA/Tanzania, and other potential data users. The questionnaires and manual were developed in English and then translated into and printed in Kiswahili.

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 his/her 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 individual interview and children under five who were to be weighed and measured. Information was also collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, ownership of various consumer goods, and use of iodised salt. Finally, the Household Questionnaire was used to collect some rudimentary information about the extent of child labour.

The Women’s Questionnaire was used to collect information from women age 15-49. These women were asked questions on the following topics: · Background characteristics (age, education, religion, type of employment) · Birth history · Knowledge and use of family planning methods · Antenatal, delivery, and postnatal care · Breastfeeding and weaning practices · Vaccinations, birth registration, and health of children under age five · Marriage and recent sexual activity · Fertility preferences · Knowledge and behaviour concerning HIV/AIDS.

The Men’s Questionnaire covered most of these same issues, except that it omitted the sections on the detailed reproductive history, maternal health, and child health. The final versions of the English questionnaires are provided in Appendix E.

Before the questionnaires could be finalised, a pretest was done in July 1999 in Kibaha District to assess the viability of the questions, the flow and logical sequence of the skip pattern, and the field organisation. Modifications to the questionnaires, including wording and translations, were made based on lessons drawn from the exercise.

Response rate

In all, 3,826 households were selected for the sample, out of which 3,677 were occupied. Of the households found, 3,615 were interviewed, representing a response rate of 98 percent. The shortfall is primarily due to dwellings that were vacant or in which the inhabitants were not at home despite of several callbacks.

In the interviewed households, a total of 4,118 eligible women (i.e., women age 15-49) were identified for the individual interview, and 4,029 women were actually interviewed, yielding a response rate of 98 percent. A total of 3,792 eligible men (i.e., men age 15-59), were identified for the individual interview, of whom 3,542 were interviewed, representing a response rate of 93 percent. The principal reason for nonresponse among both eligible men and women was the failure to find them at home despite repeated visits to the household. The lower response rate among men than women was due to the more frequent and longer absences of men.

The response rates are lower in urban areas due to longer absence of respondents from their homes. One-member households are more common in urban areas and are more difficult to interview because they keep their houses locked most of the time. In urban settings, neighbours often do not know the whereabouts of such people.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling 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 TRCHS 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 TRCHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the TRCHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the TRCHS is the ISSA Sampling Error Module (SAMPERR). This module used the Taylor linearisation method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rate

Note: See detailed sampling error

The dataset and list of questionnaires for digital literacy and entrepreneurial behavior towards tourism workers Bali

Abstract

Household Income and Expenditure Survey (HIES) collects a wealth of information on HH income and expenditure, such as source of income by industry, HH expenditure on goods and services, and income and expenditure associated with subsistence production and consumption. In addition to this, HIES collects information on sectoral and thematic areas, such as education, health, labour force, primary activities, transport, information and communication, transfers and remittances, food expenditure (as a proxy for HH food consumption and nutrition analysis), and gender.

The Pacific Islands regionally standardized HIES instruments and procedures were adopted by the Government of Tokelau for the 2015/16 Tokelau HIES. These standards were designed to feed high-quality data to HIES data end users for:

1. deriving expenditure weights and other useful data for the revision of the consumer price index;
2. supplementing the data available for use in compiling official estimates of various components in the System of National Accounts;
3. supplementing the data available for production of the balance of payments; and
4. gathering information on poverty lines and the incidence of poverty in Tokelau.

The data allow for the production of useful indicators and information on the sectors covered in the survey, including providing data to inform indicators under the UN Sustainable Development Goals (SDGs). This report, the above listed outputs, and any thematic analyses of HIES data, collectively provide information to assist with social and economic planning and policy formation.

Geographic coverage

National coverage.

Analysis unit

Households and Individuals.

Universe

The universe of the 2015/16 Tokelau Household Income and Expenditure Survey (HIES) is all occupied households (HHs) in Tokelau. HHs are the sampling unit, defined as a group of people (related or not) who pool their money, cook and eat together. It is not the physical structure (dwelling) in which people live. The HH must have been living in Tokelau for a period of six months, or have had the intention to live in Tokelau for a period of twelve months in order to be included in the survey.

Household members covered in the survey include: -usual residents currently living in the HH; -usual residents who are temporarily away (e.g., for work or a holiday); -usual residents who are away for an extended period, but are financially dependent on, or supporting, the HH (e.g., students living in school dormitories outside Tokelau, or a provider working overseas who hasn't formed or joined another HH in the host country) and plan to return; -persons who frequently come and go from the HH, but consider the HH being interviewed as their main place of stay; -any person who lives with the HH and is employed (paid or in-kind) as a domestic worker and who shares accommodation and eats with the host HH; and -visitors currently living with the HH for a period of six months or more.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2015/16 Tokelau Household Income and Expenditure Survey (HIES) sampling approach was designed to generate reliable results at the national level. That is, the survey was not designed to produce reliable results at any lower level, such as for the three individual atolls. The reason for this is partly budgetary constraint, but also because the HIES will serve its primary objectives with a sample size that will provide reliable national aggregates.

The sampling frame used for the random selection of HHs was from December 2013, i.e. the HH listing updated in the 2013 Population Count.

The 2015/16 Tokelau HIES had a quota of 120 HHs. The sample covered all three populated atolls in Tokelau (Fakaofo, Nukunonu and Atafu) and the sample was evenly allocated between the three atoll clusters (i.e., 40 HHs per atoll surveyed over a ten-month period). The HHs within each cluster were randomly selected using a single-stage selection process.

In addition to the 120 selected HHs, 60 HHs (20 per cluster) were randomly selected as replacement HHs to ensure that the desired sample was met. The replacement HHs were only approached for interview in the case that one of the primarily selected HHs could not be interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for this Household Income and Expenditure Survey (HIES) are composed of a diary and 4 modules published in English and in Tokelauan. All English questionnaires and modules are provided as external resources.

Here is the list of the questionnaires for this 2015-2016 HIES: - Diary: week 1 an 2; - Module 1: Demographic information (Household listing, Demographic profile, Activities, Educational status, Communication status...); - Module 2: Household expenditure (Housing characteristics, Housing tenure expenditure, Utilities and communication, Land and home...etc); - Module 3: Individual expenditure (Education, Health, Clothing, Communication, Luxury items, Alcohonl & tobacco); - Module 4: Household and individual income (Wages and salary, Agricultural and forestry activities, Fishing gathering and hunting activities, livestock and aquaculture activities...etc).

Cleaning operations

All inconsistencies and missing values were corrected using a variety of methods: 1. Manual correction: verified on actual questionnaires (double check on the form, questionnaire notes, local knowledge, manual verifications) 2. Subjective: the answer is obvious and be deducted from other questions 3. Donor hot deck: the value is imputed based on similar characteristics from other HHs or individuals (see example below) 4. Donor median: the missing or outliers were imputed from similar items reported median value 5. Record deletion: the record was filled by mistake and had to be removed.

Several questions used the hotdeck method of imputation to impute missing and outlying values. This method can use one to three dimensions and is dependent on which section and module the question was placed. The process works by placing correct values in a coded matrix. For example in Tokelau the “Drink Alcohol” questions used a three dimension hotdeck to store in-range reported data. The constraining dimensions used are AGE, SEX and RELATIONSHIP questions and act as a key for the hotdeck. On the first pass the valid yes/no responses are place into this 3-dimension hotdeck. On the second pass the data in the matrix is updated one person at a time. If a “Drink Alcohol” question contained a missing response then the person's coded age, sex and relationship key is searched in the “valid” matrix. Once a key is found the result contained in the matrix is imputed for the missing value. The first preferred method to correct missing or outlying data is the manual correction (trying to obtain the real value, it could have been miss-keyed or reported incorrectly). If the manual correction was unsuccessful at correcting the values, a subjective approach was used, the next method would be the hotdeck, then the donor median and the last correction is the record deletion. The survey procedure and enumeration team structure allow for in-round data entry, which gives the field staff the opportunity to correct the data by manual review and by using the entry system-generated error messages. This process was designed to improve data quality. The data entry system used system-controlled entry, interactive coding and validity and consistency checks. Despite the validity and consistency checks put in place, the data still required cleaning. The cleaning was a two-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database, consisting of: Person level record - characteristics of every (household) HH member, including activity and education profile; HH level record - characteristics of the dwelling and access to services; Final aggregated income - all HH income streams, by category and type; Final aggregated expenditure - all HH expenditure items, by category and type.

The cleaning was a two-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database.

Response rate

Overall, 99% of the response rate objective was achieved.

Sampling error estimates

Refer to Appendix 2 of the Tokelau 2015/2016 Household Income and Expenditure Survey report attached as an external resource.

This dataset contains the data of the survey waves from age 11 to 20 (K4-K8) of the target population. The following documents help to understand the content of the data (partially restricted access):

• Handbook K4-K8 in two versions: Short version (public access) containing general information such as descriptions of questionnaire themes, source, derived constructs, and key publications ("K4-8_Handbook_short") and a long version providing a detailed overview of each scale, and item wordings ("K4-8_Handbook_long”). • Overview of standard variables (e.g., sex, SES, treatment allocation) that are part of every data package on SWISSUbase • Codebooks (questionnaires with question/variable names) in English • Original questionnaires in German • Scale syntaxes (SPSS) for each data collection wave • File info including all variable/value labels and dataset structure • Description of the z-proso project, containing general information on the project, methods and data ("z-proso_ProjectOverview", public access) • Tabular overview on all z-proso project phases, data collections, and questionnaires including information on scales/domains, and page numbers in the original German questionnaires ("z-proso_DataCollectionsInstruments_W1-9", public access) • A publication list with selected z-proso methods publications (public access)

The datafile is available in the CSV, SAV (SPSS), and DTA (STATA) formats.

The data is available with prior agreement of project co-directors (Manuel Eisner, Denis Ribeaud, Lilly Shanahan) only. The project direction will grant access to the data based on a research proposal. The research proposal needs to be in the form of a project description with the following components: research questions and hypotheses, operationalisation, planned publications, linking with other project or other data (if planned). If you have questions or need more detailed information or additional documentation, do not hesitate to contact the project direction (z-proso@jacobscenter.uzh.ch). The research proposal is part of the application form.

If you, as a data user, are or were a z-proso participant yourself (focal participant, primary caregiver, or teacher), you are required to contact us before submitting a proposal.

If you require further data from earlier data collections, or from other informants (parent, teacher), or from add-on data collections that are not (yet) available on SWISSUbase, please provide a brief outline of your research questions along with a rationale for your specific data requirements.

Abstract

The Jordan Population and Family Health Survey (JPFHS) is part of the worldwide Demographic and Health Surveys Program, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 2012 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, mortality, family planning, and fertility preferences, as well as maternal and child health and nutrition, that can be used by program managers and policymakers to evaluate and improve existing programs. The JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The 2012 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and for the two special domains: the Badia areas and people living in refugee camps. To facilitate comparisons with previous surveys, the sample was also designed to produce estimates for the three regions (North, Central, and South). The grouping of the governorates into regions is as follows: the North consists of Irbid, Jarash, Ajloun, and Mafraq governorates; the Central region consists of Amman, Madaba, Balqa, and Zarqa governorates; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba governorates.

The 2012 JPFHS sample was selected from the 2004 Jordan Population and Housing Census sampling frame. The frame excludes the population living in remote areas (most of whom are nomads), as well as those living in collective housing units such as hotels, hospitals, work camps, prisons, and the like. For the 2004 census, the country was subdivided into convenient area units called census blocks. For the purposes of the household surveys, the census blocks were regrouped to form a general statistical unit of moderate size (30 households or more), called a "cluster", which is widely used in surveys as a primary sampling unit (PSU).

Stratification was achieved by first separating each governorate into urban and rural areas and then, within each urban and rural area, by Badia areas, refugee camps, and other. A two-stage sampling procedure was employed. In the first stage, 806 clusters were selected with probability proportional to the cluster size, that is, the number of residential households counted in the 2004 census. A household listing operation was then carried out in all of the selected clusters, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. In the second stage of selection, a fixed number of 20 households was selected in each cluster with an equal probability systematic selection. A subsample of two-thirds of the selected households was identified for anthropometry measurements.

Refer to Appendix A in the final report (Jordan Population and Family Health Survey 2012) for details of sampling weights calculation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 JPFHS used two questionnaires, namely the Household Questionnaire and the Woman’s Questionnaire (see Appendix D). The Household Questionnaire was used to list all usual members of the sampled households, and visitors who slept in the household the night before the interview, and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of the household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and the availability of durable goods. Moreover, the questionnaire included questions about child discipline. The Household Questionnaire was also used to identify women who were eligible for the individual interview (ever-married women age 15-49 years). In addition, all women age 15-49 and children under age 5 living in the subsample of households were eligible for height and weight measurement and anemia testing.

The Woman’s Questionnaire was administered to ever-married women age 15-49 and collected information on the following topics: • Respondent’s background characteristics • Birth history • Knowledge, attitudes, and practice of family planning and exposure to family planning messages • Maternal health (antenatal, delivery, and postnatal care) • Immunization and health of children under age 5 • Breastfeeding and infant feeding practices • Marriage and husband’s background characteristics • Fertility preferences • Respondent’s employment • Knowledge of AIDS and sexually transmitted infections (STIs) • Other health issues specific to women • Early childhood development • Domestic violence

In addition, information on births, pregnancies, and contraceptive use and discontinuation during the five years prior to the survey was collected using a monthly calendar.

The Household and Woman’s Questionnaires were based on the model questionnaires developed by the MEASURE DHS program. Additions and modifications to the model questionnaires were made in order to provide detailed information specific to Jordan. The questionnaires were then translated into Arabic.

Anthropometric data were collected during the 2012 JPFHS in a subsample of two-thirds of the selected households in each cluster. All women age 15-49 and children age 0-4 in these households were measured for height using Shorr height boards and for weight using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children in the field to measure their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Cleaning operations

Fieldwork and data processing activities overlapped. Data processing began two weeks after the start of the fieldwork. After field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman, where they were registered and stored. Special teams were formed to carry out office editing and coding of the openended questions.

Data entry and verification started after two weeks of office data processing. The process of data entry, including 100 percent reentry, editing, and cleaning, was done by using PCs and the CSPro (Census and Survey Processing) computer package, developed specially for such surveys. The CSPro program allows data to be edited while being entered. Data processing operations were completed by early January 2013. A data processing specialist from ICF International made a trip to Jordan in February 2013 to follow up on data editing and cleaning and to work on the tabulation of results for the survey preliminary report, which was published in March 2013. The tabulations for this report were completed in April 2013.

Response rate

In all, 16,120 households were selected for the survey and, of these, 15,722 were found to be occupied households. Of these households, 15,190 (97 percent) were successfully interviewed.

In the households interviewed, 11,673 ever-married women age 15-49 were identified and interviews were completed with 11,352 women, or 97 percent of all eligible women.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2012 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2012 JPFHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012 JPFHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer

Abstract

The Bangladesh Demographic and Health Survey (BDHS) is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health.

The BDHS is intended to serve as a source of population and health data for policymakers and the research community. In general, the objectives of the BDHS are to: - assess the overall demographic situation in Bangladesh, - assist in the evaluation of the population and health programs in Bangladesh, and - advance survey methodology.

More specifically, the objective of the BDHS is to provide up-to-date information on fertility and childhood mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; nutrition levels; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programs and strategies for improving health and family planning services in the country.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 10-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

Bangladesh is divided into six administrative divisions, 64 districts (zillas), and 490 thanas. In rural areas, thanas are divided into unions and then mauzas, a land administrative unit. Urban areas are divided into wards and then mahallas. The 1996-97 BDHS employed a nationally-representative, two-stage sample that was selected from the Integrated Multi-Purpose Master Sample (IMPS) maintained by the Bangladesh Bureau of Statistics. Each division was stratified into three groups: 1 ) statistical metropolitan areas (SMAs), 2) municipalities (other urban areas), and 3) rural areas. 3 In the rural areas, the primary sampling unit was the mauza, while in urban areas, it was the mahalla. Because the primary sampling units in the IMPS were selected with probability proportional to size from the 1991 Census frame, the units for the BDHS were sub-selected from the IMPS with equal probability so as to retain the overall probability proportional to size. A total of 316 primary sampling units were utilized for the BDHS (30 in SMAs, 42 in municipalities, and 244 in rural areas). In order to highlight changes in survey indicators over time, the 1996-97 BDHS utilized the same sample points (though not necessarily the same households) that were selected for the 1993-94 BDHS, except for 12 additional sample points in the new division of Sylhet. Fieldwork in three sample points was not possible (one in Dhaka Cantonment and two in the Chittagong Hill Tracts), so a total of 313 points were covered.

Since one objective of the BDHS is to provide separate estimates for each division as well as for urban and rural areas separately, it was necessary to increase the sampling rate for Barisal and Sylhet Divisions and for municipalities relative to the other divisions, SMAs and rural areas. Thus, the BDHS sample is not self-weighting and weighting factors have been applied to the data in this report.

Mitra and Associates conducted a household listing operation in all the sample points from 15 September to 15 December 1996. A systematic sample of 9,099 households was then selected from these lists. Every second household was selected for the men's survey, meaning that, in addition to interviewing all ever-married women age 10-49, interviewers also interviewed all currently married men age 15-59. It was expected that the sample would yield interviews with approximately 10,000 ever-married women age 10-49 and 3,000 currently married men age 15-59.

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

Mode of data collection

Face-to-face

Research instrument

Four types of questionnaires were used for the BDHS: a Household Questionnaire, a Women's Questionnaire, a Men' s Questionnaire and a Community Questionnaire. The contents of these questionnaires were based on the DHS Model A Questionnaire, which is designed for use in countries with relatively high levels of contraceptive use. These model questionnaires were adapted for use in Bangladesh during a series of meetings with a small Technical Task Force that consisted of representatives from NIPORT, Mitra and Associates, USAID/Bangladesh, the International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B), Population Council/Dhaka, and Macro International Inc (see Appendix D for a list of members). Draft questionnaires were then circulated to other interested groups and were reviewed by the BDHS Technical Review Committee (see Appendix D for list of members). The questionnaires were developed in English and then translated into and printed in Bangla (see Appendix E for final version in English).

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 his/her 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 itself, such as the source of water, type of toilet facilities, materials used to construct the house, and ownership of various consumer goods.

The Women's Questionnaire was used to collect information from ever-married women age 10-49. These women were asked questions on the following topics: - Background characteristics (age, education, religion, etc.), - Reproductive history, - Knowledge and use of family planning methods, - Antenatal and delivery care, - Breastfeeding and weaning practices, - Vaccinations and health of children under age five, - Marriage, - Fertility preferences, - Husband's background and respondent's work, - Knowledge of AIDS, - Height and weight of children under age five and their mothers.

The Men's Questionnaire was used to interview currently married men age 15-59. It was similar to that for women except that it omitted the sections on reproductive history, antenatal and delivery care, breastfeeding, vaccinations, and height and weight. The Community Questionnaire was completed for each sample point and included questions about the existence in the community of income-generating activities and other development organizations and the availability of health and family planning services.

Response rate

A total of 9,099 households were selected for the sample, of which 8,682 were successfully interviewed. The shortfall is primarily due to dwellings that were vacant or in which the inhabitants had left for an extended period at the time they were visited by the interviewing teams. Of the 8,762 households occupied, 99 percent were successfully interviewed. In these households, 9,335 women were identified as eligible for the individual interview (i.e., ever-married and age 10-49) and interviews were completed for 9,127 or 98 percent of them. In the half of the households that were selected for inclusion in the men's survey, 3,611 eligible ever-married men age 15-59 were identified, of whom 3,346 or 93 percent were interviewed.

The principal reason for non-response among eligible women and men was the failure to find them at home despite repeated visits to the household. The refusal rate was low.

Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling 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 BDHS to minimize this type of error, non-sampling 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 BDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the BDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the BDHS is the ISSA Sampling Error Module. This module used the Taylor

This dataset is the result of an online survey the authors conducted in the German agricultural science community in 2020. The survey inquires not only about the status quo, but also explicitly about the wishes and needs of users, representing the agricultural scientific research domain, of the in-progress NFDI (national research data infrastructure). Questions cover information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in research data management in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. In total, the questionnaire contained 52 questions and was conducted using the Community Edition of the Open Source Survey Tool LimeSurvey (Version 3.19.3; LimeSurvey GmbH). The questions were accessible in English and German. The first set of questions (Questions 1-4) addressed the respondent’s professional background (i.e. career status, affiliation and subject area, but no personal data) and the user group. The user groups included data users, data providers as well as infrastructure service and information service providers. Subsequent questions were partly user group specific. All questions, the corresponding question types and addressed user groups can be found in the questionnaire files (Survey-Questions-2020-DE.pdf German Version; Survey-Questions-2020-EN.pdf English Version). The survey was accessible online between June 26th and July 21st 2020, could be completed anonymously and took about 20 minutes. The survey was promoted in an undirected manner via mail lists of agricultural institutes and agricultural-specific professional societies in Germany, via social media (e.g. Twitter) and announced during the first community workshop of NFDI4Agri on July 15th 2020 and other scientific events. After closing the survey, we exported the data from the LimeSurvey tool and initially screened it. We considered all questionnaires that contained at least one answered question in addition to the respondent’s professional background information (Questions 1-4). In total, we received 196 questionnaires of which 160 were completed in full (although not always every answer option was used, empty cells are filled with “N/A”). The main data set contains all standardized answers from the respondents. For anonymization, respondents’ individual answers, for instance, free text answers, comments and details in the category "other” were removed from the main data set. The main data set only lists whether such information was provided (“Yes”) or not (“No” or “N/A”). In an additional file respondents’ individual answers of the questions 4-52 are listed alphabetically, so that it is not possible to trace the data back. In the rare cases where only one person has provided such individual information in an answer, it is traceable but does not contain any sensitive data. The main data set containing answers of the 196 questionnaires received can be found in the file Survey-2020-Main-DataSet-Answers.xlsx. The subsidary data set containing the respondents’ individual answers (most answers are in German and are not translated) of the questions 4-52, for instance, free text answers, comments and details in the category "other” (alphabetically listed) can be found in Survey-2020-Subsidary-DataSet-Free_Text_Answers.xlsx.

Abstract

The 1996 Papua New Guinea household survey is designed to measure the living standards of a random sample of PNG households. As well as looking at the purchases, own-production, gift giving/receiving and sales activities of households over a short period (usually 14 days), the survey also collects information on education, health, nutrition, housing conditions and agricultural activities. The survey also collects information on community level access to services for education, health, transport and communication, and on the price levels in each community so that the cost of living can be measured.

There are many uses of the data that the survey collects, but one main aim is for the results to help government, aid agencies and donors have a better picture of living conditions in all areas of PNG so that they can develop policies and projects that help to alleviate poverty. In addition, the survey will provide a socio-economic profile of Papua New Guinea, describing the access that the population has to agricultural, educational, health and transportation services, their participation in various economic activities, and household consumption patterns.

The survey is nationwide and the same questionnaire is being used in all parts of the country, including the urban areas. This fact can be pointed out if households find that some of the questions are irrelevant for their own living circumstances: there are at least some Papua New Guinean households for which the questions will be relevant and it is only by asking everyone the same questions that living standards can be compared.

Geographic coverage

The survey covers all provinces except Noth Solomons.

Analysis unit

• Household
• Individual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Listing Form and Selection of the Sample Listing of households is the first job to be done after the team has settled in and completed the introductions to the community. Listing is best done by the whole team working together. This way they all get to know the community and its lay-out. However, if the census unit is too large this wastes too much time. So before beginning asks how many households there are, very roughly, in the census unit (noting that teams are supplied with the number of households that were there in the 1990 census). If the answer is 80 or more, divide the team into two and have each half-team work on one sector of the community/village. See the section below on what to do when the listing work is divided up.

If the census unit is a "line-up point" that does not correspond to any single village or community the number of households will often exceed 200 and frequently they are also quite dispersed. In this case it is not practical to attempt to list the whole census unit, so a decision is made in advance to split the census unit into smaller areas (perhaps groupings of clans). First, a local informant must communicate the boundaries of the census unit and for natural or administrative sub-units with the larger census unit (such as hamlets; or canyons/valleys). The sub-units should be big enough to allow for the selection of a set of households (about 30 or more), but should not be so large that excessive transport time will be needed each day just to find the household. Once the subunit is defined, its boundaries should be clearly described. Then one of the smaller units is randomly selected and the procedures outlined above are then followed to complete the listing. Note: only one of the sub-units are listed, sample chosen, and interviews undertaken.

The most important thing in the listing is to be sure that you list all the households and only the households belonging to the named village or census unit (or subset of the census unit if it is a line-up point). In rural areas, explain to village leaders at the beginning: "We have to write down all the households belonging to (Name) village." In case of doubt, always ask: "Does this household belong to (Name) village?" In the towns, the selected area is shown on a map. Check that the address where you are listing is within the same area shown.

Also explain: "We only write down the name of the head of household. When we have the list of all the households, we will select 12 by chance, for interview."

Procedure for Listing The listing team walks around in every part of the village, accompanied by a guide who is a member of the village. If possible, find a person who conducted the 1990 Census in this community or someone with similar knowledge of the community and ask them to be your guide. Make sure you go to all parts of the village, including outlying hamlets. In hamlets, on in any place far from the centre, always check: "Do these people belong to (Name) village?"

In every part of the village, ask the guide about every house: "Who lives in this house? What is the name of the household head?" Note that you do not have to visit every household. At best, you just need to see each house but you do not need to go inside it or talk to anyone who lives there. Even the rule of seeing each house may be relaxed if there are far away household for which good information can be provided by the guide.

Enter the names of household heads in the lines of the listing form. One line is used for each household. As the lines are numbered, the procedure gives a number to each household. When you come to the last house, check with the guide: "Are you sure we have seen all the houses in the village?"

NOTE: It does not matter in what order you list the households as long as they are all listed. After the listing is complete, check that all lines are numbered consecutively with no gaps, from start to finish. The number on the last line should be exactly the number of households listed.

Note: If the list is long (say more than 30 households) interviewer may encounter difficulties when looking for their selected household. One useful way to avoid this is to show the approximately the place in the list here certain landmarks come. This can be done by writing in the margin, CHURCH or STORE or whatever. You can also indicate where the lister started in a hamlet, for example.

Sample Selection The sampling work is done by the supervisor. The first steps are done at the foot of the first page of the listing form. The steps to be taken are as follows:

1. Fill in the numbers asked for at the foot of the last listing page, as follows:
2. M: enter the total number of households listed (same as last household number shown).
3. Interval L: calculate (M / 15) to the nearest whole number.
4. R: This is a random number with 3-digit decimals between 0.000 and 0.999.

5. MR: multiply M by R and round to the nearest whole number. (If decimal 0.5, round up).

6. MR gives the 1st selection. (Exception: If MR=0, L gives the first selection.) Enter S against this line in the selection column of the list.

7. Count down the list, beginning after the 1st selection, a distance of L lines to get the 2nd selection, then another L to get the 3rd, etc. When you come to the bottom of the list, jump back to the top as if the list were circular. Stop after the 15th selection. Mark the 13th, 14th, and 15th selections "RES" (for reserve). Mark the 1st - 12th selection "S" (for selection).

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1996 Papua New Guinea Household Survey questionnaire consists of three basic parts:

Household questionnaire first visit: asks a series of questions about the household, discovering who lives there, what they do, their characteristics, where they live, and a little about what kinds of things they consume. This questionnaire consists of the following sections. - Section 1. Household Roster - Section 2. Education - Section 3. Income Sources - Section 4. Health - Section 5. Foods in the Diet - Section 6. Housing Conditions - Section 7. Agricultural Assets, Inputs and Services - Section 8. Anthropometrics - Section 9. Household Stocks

Consumption recall (second visit questionnaire): is focused primarily on assessing the household's expenditure, gift giving and recieving, production, and level of wealth. The information in the first and second visits will provide information that can determine the household's level of consumption, nutrition, degree of food security, and ways in which it organizes its income earning activities. This questionnaire consists of the following sections. - Section 1. Purchases of Food - Section 2. Other Frequent Purchases - Section 3. Own-production of Food - Section 4. Gifts Received: Food and Frequent Purchases (START) - Section 5. Annual Expenses and Gifts - Section 6. Inventory of Durable Goods - Section 7. Inward Transfers of Money - Section 8. Outward Transfers of Money - Section 9. Prices - Section 10. Repeat of Anthropometric Measurements - Section 11. Quality of Life

Community Questionnaire: which is completed by the interview team in consultation with community leaders. This questionnaire also includes market price surveys that are carried out by the team when they are working in the community. Associated with this is a listing of all households in the community, which has to be done prior to the selection of the 12 households. This questionnaire consists of the following sections. - Section A. Listing of Community Assets - Section B. Education - Section C. Health - Section D. Town or Government Station - Section E: Transport and Communications - Section F. Prices - Section G. Changes in Economic Activity, Infrastructure, and Services

Brand performance data collected from AI search platforms for the query "post-purchase survey questions list".

Abstract

The 2015-2016 Turkmenistan Multiple Indicator Cluster Survey (MICS), conducted between September 2015 and January 2016 by the State Committee of Statistics of Turkmenistan. Financial support was provided by the Government of Turkmenistan and United Nations Children’s Fund (UNICEF), with additional support of the United Nations Population Fund (UNFPA). Technical support was provided by UNICEF.

The 2015-2016 Turkmenistan MICS is a nationally representative survey of 6,101 households, of which 5,974 were found to be occupied. Of these, 5,861 were successfully interviewed for a household response rate of 98 percent. In the interviewed households 7,693 women (age 15-49 years) were identified and 3,785 children under age five. Individual questionnaires were completed for 7,618 women and for 3,765 children. The sample allows for the estimation of some key indicators at the national level, for urban and rural areas, and for 6 regions (Ashgabat city and 5 velayats).

The 2015-2016 Turkmenistan MICS is expected to contribute to the evidence base of several important policies and strategies as well as to form part of the baseline data for the post-2015 era, in particular for monitoring progress towards the Sustainable Development Goals (SDGs).

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

The survey covered all de jure household members (usual residents), all women aged between 15-49 years, all children under 5 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the 2015-2016 Turkmenistan MICS was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the six regions of the country: Ashgabat city (capital) and five velayats (regions) – Ahal, Balkan, Dashoguz, Lebap and Mary. Urban and rural areas in each of the five velayats (regions) in addition to Ashgabat city (only urban) were defined as the sampling strata (11 main strata).

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

The sample size for the 2015- 2016 Turkmenistan MICS was calculated as 6,200 households. For the calculation of the sample size, the key indicator used was the percentage of married women using a contraceptive method from the 2006 Turkmenistan MICS.

The number of households selected per cluster for the 2015-2016 Turkmenistan MICS was determined as 20 households, based on a number of considerations, including a review of the design effects for the estimates of key indicators from the 2006 Turkmenistan MICS data, the budget available, and the time that would be needed per team to complete one cluster.

Selection of 20 households in each sample segment in all regions, resulted in a total target sample of 310 segments and 6200 households. Within each region the sample was allocated proportionately to the urban and rural strata.

For the first sampling stage, the enumeration areas were defined as PSUs selected within each stratum (region, urban/rural) systematically with PPS from the ordered list of PSUs in the sampling frame. The measures of size for the enumeration areas were based on the number of households identified in the sampling frame of the 2012 Census. The PSUs within each stratum were ordered geographically, in order to provide implicit geographic stratification and ensure a proportional distribution of the sample to all parts of the region.

Since the sampling frame (the 2012 Census) was not up-to-date, a new listing of households was conducted in all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were formed who visited all of the selected enumeration areas and listed all households in the enumeration areas.

Listing training was held in the period 16-19 June 2015 (4 days) in Ashgabat city. The training was attended by 3 cartographers, 3 listers, 1 reserve and 1 supervisor from each velayat/Ashgabat city (in total 48 participants). The training program consisted of two parts, the first 1.5 days for theoretical knowledge followed by 1.5 days for conducting a pilot in the field – to implement acquired knowledge into practice.

During the period from 22 June to 16 July 2015 in all regions of Turkmenistan work on the mapping and household listing in the clusters for the MICS was carried out in accordance with the schedule of activities developed by the State Statistical Committee of Turkmenistan. During the listing the following materials were used: - Manual for Mapping and Household Listing - Listing Forms - Schematic maps from the 2012 Census in printed form.

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to n (the total number of households in each enumeration area) at the State Statistical Committee of Turkmenistan, where the selection of 20 households in each enumeration area was carried out using random systematic selection procedures.

The sampling procedures are more fully described in "Multiple Indicator Cluster Survey 2015-16 - Final Report" pp.182-185.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Generic MICS were structured questionnaires based on the MICS5 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes List of Household Members, Education, Child Labour, Child Discipline, Household Characteristics, Water and Sanitation, Handwashing, and Salt Iodization.

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

The women's questionnaire includes Woman's Background, Access to Mass Media and Use of Information/Communication Technology, Fertility/Birth History, Desire for Last Birth, Maternal and Newborn Health, Post-natal Health Checks, Illness Symptoms, Marriage/Union13, Contraception, Unmet Need, Attitudes Toward Domestic Violence and HIV/AIDS.

The children's questionnaire includes Child's Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness and Anthropometry.

From the MICS5 model English and Russian version, the questionnaires were customised and translated into the Turkmen language and were pre-tested. A pre-test of the paper version of questionnaires in Russian and Turkmen languages (first pre-test, 12 days) was conducted in Ahal velayat (rural area) and Ashgabat city in July 2015. 200 households were interviewed – 100 using the Turkmen language questionnaires and 100 using Russian language questionnaires. A second pre-test was conducted in August 2015 in 100 households using tablets with revised questionnaires. Based on the results of the pre-tests, modifications were made to the wording and translation of the questionnaires as well as in the application for tablets.

Cleaning operations

Data were entered using the CSPro software, Version 5.0. Data collection was carried out on tablets by 37 interviewers and 6 supervisors. Using a tablets facilitated many tasks related to control and management, including: - assigning households to the interviewers, - receiving collected data from the interviewers, - checking household questionnaires and individual questionnaires, - finalising the cluster, - preparing the data files to be sent to the Central Office.

Procedures and standard programs developed under the global MICS programme and adapted to the 2015-2016 Turkmenistan MICS questionnaire were used throughout. Data processing began simultaneously with data collection in September 2015 and was completed in January 2016. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose.

Regular monitoring of the data collection and other relevant processes was carried out by UNICEF staff, consultants (both national and international) as well as by management and staff of the State Committee of Statistics (Turkmenstat) responsible for implementation of the 2015-2016 Turkmenistan MICS.

Response rate

Of the 6,100 households selected for the sample, one dwelling unit was found to be occupied by two households, leading to a total of 6,101 households in the final sample. Of the 6,101 households, 5,974 were found to be occupied. Of these, 5,861 were successfully interviewed for a household response rate of 98 percent. In the interviewed households 7,693 women (age 15-49 years) were identified. Of these, 7,618 were successfully interviewed, yielding a response rate of 99 percent within the interviewed households. There were 3,785 children under age five listed in the household questionnaires. Questionnaires were completed for 3,765 of these children, which corresponds to a response rate of almost 100 percent within interviewed households. Overall response rates of 97 and 98 percent are calculated for the individual interviews of women and under-5s, respectively.

Sampling error estimates

Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically

The dataset provides material relating to a questionnaire entitled "Semantic Web: Perspectives". This questionnaire was addressed to the W3C Semantic Web mailing list (semantic-web@w3.org) and was open to responses from May 12th to May 25th, 2019. A total of 113 responses were collected in this time. The following files are provided:

public-comments.txt: provides the public comments of respondents in plain text;

questionnaire-form.pdf: illustrates the design of the questionnaire, including questions, types of responses permitted, etc.;

questionnaire-responses.tsv: lists the individual responses (without private comments) as a tab-separated values file;

success-keywords.xlsx: provides a spreadsheet mapping success story responses to a list of keywords, further providing statistics on these keywords;

wordcloud-bw.svg: provides a word-cloud of success-story keywords in black & white;

wordcloud-colour.svg: provides a word-cloud of success-story keywords in colour.

The word-clouds were produced using Jason Davies' online service, copying and pasting the keywords from the success-keywords.xlsx spreadsheet (e.g., Column A, Sheet Statistics) into the text field; the following settings were selected: Orientations from 0° to 0°, Spiral: Rectangular; Scale: n; Number of words: 400; One word per line: ticked; Font: Patua One (must be installed locally beforehand). The resulting SVG files were later modified in a text editor to add a link to the font used, to tighten the bounding box, and to produce a black & white version.

We thank the respondents for providing their input.

This questionnaire consists of 33 items based on a part of the dissertation, have gone psychometric properties test and validity by CFA.

Abstract

A comprehensive and detailed statistical database of any economic activity is a prerequisite for planning and policy making and this applies to economic activities that play a major role in most modern world economies.

The Palestinian Central Bureau of Statistics is pleased to issue the twenty-three volume of the Economic Survey of Palestine, including statistical tables of findings. This edition presents the findings of the surveys conducted for 2017 as the reference year and covers most of the economic activities operating in Palestine since 1994. Economic surveys of various fields constitute the basic foundations for the compilation of National Accounts for Palestine

Geographic coverage

Palestine

Analysis unit

Enterprises

Universe

The twenty third round of the economic survey series was conducted based on the Establishments Census of 2017 as a sampling frame. The economic surveys series covered activities in accordance with ISIC-4 (fifth digits).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the economic surveys series was One-Stage Stratified Systematic Random Sample in which enterprises were divided into two types: the first type covered overall enterprises taken comprehensively, the second type covered enterprises selected in a systematic random way in which the enterprise constituted the sampling unit. Three levels of strata were used to draw up an efficient representative sample. 1. The frame is separated into two geographical locations: the West Bank excludes those parts of Jerusalem which were annexed by Israeli occupation in 1967, and the Gaza Strip. 2. Strata are created based on the fourth digit of ISIC-4, exclude services sector based on the second in which every activity presents actual stratum. 3. Within each stratum, new strata are created according to employment size.

The sample size in Palestine (excludes those parts of Jerusalem which were annexed by Israeli occupation in 1967) in 2017 was 9,916 enterprises out of 136,425 enterprises comprising the survey sampling frame.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The design of the 2017 questionnaire took into account the major economic variables pertaining the sector examined and met with the National Accounts for Palestine according to SNA 2008. All of the economic surveys series used the same questionnaire, with a few different characteristics pertaining to each survey. The questionnaire included these variables: 1. Number of employed persons and compensation of employees. 2. Value of output from the main activity and the secondary activities. 3. Production inputs of goods and services. 4. Fees, taxes and subsidies on production. 5. Assets and capital formation.

Cleaning operations

There are two steps: First: The entering program for PC-Tablets was designed to prevent entering any contrasting data during data entry. Second: List of questionnaires that included errors related to the logically of the data after entering the data by field worker.

Response rate

Response rate: 96.1%.

Sampling error estimates

Sampling Errors Data of this survey affected by sampling errors due to use of the sample and. Therefore, certain differences were expected in comparison with the real values obtained through censuses. Variance were calculated for the most important indicators as shown in tables below. Dissemination of results at the national level did not pose a problem, but there was high variance in some variables.

Non Sampling Error These types of errors could appear on one or on all of the survey stages that include data collection and data entry; they related to, respondents, fieldworkers, and data entry personnel. To avoid errors and mitigate their impact, a number of procedures were applied to enhance the accuracy of the data through a process of data collection from the field and data processing.

List of tables and questionnaires (supplemental material to JAAD research article "Variation in initial biopsy technique for primary melanoma diagnosis: a population-based cohort study in New South Wales, Australia")

Abstract

The main purpose of the KPMS surveys is to provide data for the study of multiple aspects of household welfare and behavior, analysis of poverty, and understanding the effect of government policies on households.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to expedite the survey process, NATSTATCOM used much of the same sample design and survey instruments as those used for the 1993 Baseline Survey. However, the Fall 1996-1998 KPMS surveys used a new sampling frame based on the Kyrgyz Household Registration System. This system was taken from the Census Posts intended for use by the first National Census of the Kyrgyz Republic. Using this system, NATSTATCOM updated the central household registration files effective January 1, 1996, and the information that was used for the sampling frame was as up to date as possible. The procedures followed in the stratification and identification of Primary Sampling Units (PSUs) were similar for all rounds of the KPMS as discussed below.

Formation of Strata

Initially the country was divided into seven (7) strata defined by oblasts (Oblasts are administrative divisions of the country which in turn are sub-divided in to Rayons) and by residence location (i.e. urban vs. rural) within oblasts. The rural portion of Bishkek oblast was combined with the rural portion of neighboring Chui oblast for stratification purposes as Bishkek has practically no rural population.

Selection of PSUs and Households

For the 1998 KPMS, a total of 255 PSUs (of which 178 were urban and 77 rural) were identified. The estimated total population was around 1.1 million of which about 421,000 was classified as urban. A minimum of 384 households per oblast was targeted in order to get a representative data at the oblast level11. This translated in to a targeted sample size of 2,688 households for the whole of the Kyrgyz Republic (i.e. 384*7 oblasts=2,688). These households were divided into urban (887 households) and rural (1,801 households). The overall projected response rate for the 1998 KPMS was also set at somewhat above 0.90. With an overall sampling rate of 1/336, this resulted in to a sample close to a target size of 3,000 households for the whole survey.

Once the strata and PSUs were formed and identified, selection of sample PSUs and households was then carried out in the following order:

1) Selection of large and small towns12 [Note: For the 1998 KPMS, large towns were defined as those with a population size of 41,125 or larger. Small towns are those with population less than 41,125. This number, according to a NATSTATCOM document was calculated as follows: n=4.7*350*25. This calculation was based on an estimated household size of 4.7, an estimated interval rate of 350 and an average work load per interviewer of 25 households. No further information is available regarding the bases of such an assumption. At the moment, we do not have information about the cut off number that separates large towns from small ones for the other two KPMS.]

2) Selection of Census Posts in urban areas

3) Selection of Ayil Kenshes (village authorities) and population points in rural areas, and

4) Selection of households from selected Census Posts and Ayil Kenshes. In the rural stratum of each oblast, villages were used as the listing units and within these listing units, equal probability sampling methods were used to select the ultimate sampling units (households). In urban areas, the centralized computer listings from various sources of household registration were used for the selection of households. These lists are categorized into four: Type 1 - Private house resident households listed by BTIs Type 2 - Public house residents listed with other organizations with dormitories only Type 3 - Public and private households listed by JSKs Type 4 - Public and private households listed by all other organizations. In some cases, private households were included in the last three public categories (Types 2, 3 and 4). However, only public households were selected from these types since it was believed that any private households listed in these category types were also included in the Type 1 category. The counts for Type 2, 3, and 4 lists were then adjusted based on the oblast estimates of all urban households.13 Prior to actual household sample selection, lists from types 2 to 4 were updated and adjusted to remove private households, so that any potential double eligibility was eliminated. Urban strata were then formed within each oblast based on type of household listing. In most cases, types had to be combined to form strata of a reasonable size.

Within the limits of rounding and requiring at least one sampling unit per stratum, the allocation of sampling units to urban strata was proportional to the number of households projected for that stratum after allowing for removal of duplicates (private households appearing on a BTI and other lists).

As for rural households, selection of urban households was done using systematic random sampling within each stratum except that more subdividing of urban lists was required before selecting the final list sample that defines each sampling unit.

Even though the list sources were identified and sampled using data as of January 1, 1996 (and using projections of unduplicated counts in some cases), the final listings were updated in the field just prior to the survey period. Therefore, the sample households in selected areas were drawn from the most current available listings.

Mode of data collection

Face-to-face [f2f]

Research instrument

The KPMS surveys were carried out using a household questionnaire and a community (population point) questionnaire. The household questionnaires were used to collect demographic information on the composition of the household, housing, household consumption including home production, as well as economic activities in agricultural and non-agricultural sectors. For each household member, individual level data on health, education, migration and labor was collected using the household questionnaires. Community questionnaires were used to collect price data and the presence of social services and infrastructure in the community (population point) where the sampled household is located.

The household questionnaire was extensive and required several hours of intense interviewing to gather all that was needed from each household and its embers. The household questionnaire was split into two parts. The first part was used to collect data through a face to face interview on household roster, dwelling, education, health, migration, etc. At the end of the first part, members who shop for food for the whole household and those who know most about income, expenditure and savings of other household members were identified and designated as respondents for the next part (second round). The second round of interview was administered two weeks after the first half and collected data on crops, food and animal products produced by the household, food expenditure and home produced food consumption.

Some sections of the household questionnaire such as those that deal with dwelling and expenditure information were administered to the person most knowledgeable of the family's overall expenditures, income and other finances as well as about the family's business activities and employment. In other sections, each adult in each sample household was interviewed individually. The information gathered from each household included extensive data on education, health, employment, migration, reproduction and reproductive health (for women aged 15 to 49), land use, expenditure, revenue and other financial matters, as well as anthropometric measurements (for children 5 years and younger). Information about children under 14 years of age was collected by asking the relevant questions to the adult household member who is primarily responsible for each child's care.

The community (Population Point) questionnaires were administered to each sample cluster. They were used to collect data on prices of goods and services, distance to schools, shopping and medical facilities, types of housing, commercial and private land use and availability of infrastructure.

HOUSEHOLD QUESTIONNAIRE

The KPMS household questionnaires generally contain 15 major sections, and each of these sections covers a separate aspect of household activity. In some cases, the section has sub-sections. These household questionnaires were designed to better assess the changing environment brought about by the advent of a market economy and to enable a more in depth analysis of topics such as housing, health, and education. The various sections of the KPMS household questionnaire are described below.The household questionnaires administered in the KPMS surveys are more or less similar with minor modifications and additions in the successive rounds of the KPMS.

POPULATION POINT QUESTIONNAIRE

The community (population point) questionnaire was used to collect information and data that are relevant to the community/population point where the household is located. The questionnaire was designed to be administered in the geographical area of each sample cluster. It was used to collect data regarding prices of goods and services in the local area and data on community infrastructure. Respondents to these questionnaires are those believed to be well informed members of the community that the interviewers identified by going to the rayon, city, oblast administration or other governmental agency located in the population point6. The

Abstract

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

Survey Objectives The 2006 Bosnia and Herzegovina (BiH) Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Bosnia and Herzegovina. - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Bosnia and Herzegovina and to strengthen technical expertise in the design, implementation, and analysis of such systems.

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

The 2006 BiH Multiple Indicator Cluster Survey also included a module referring to household income and expenditure within the household questionnaire.

Survey Implementation The survey was carried out by Ministry of Health and Social Welfare Republika Srpska and FBiH Public Health Institute, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

Geographic coverage

The survey is nationally representative and covers the whole of Bosnia and Herzegovina.

Analysis unit

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

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

Women aged 15-49

Children aged 0-4

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2006 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2006 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2006 MICS was to provide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates for each of the two entities: the Federation of Bosnia and Herzegovina (FBiH) and the Republika Srpska (RS) for key indicators (owing to the constraints in the survey budget, the Brcko District is represented in the same way as other municipalities in BiH). Each entity is subdivided into municipalities. In addition municipalities in Federation of BiH are grouped into 10 cantons. Each municipality is divided into settlements, settlements into statistical circles and each circle into enumeration areas. In total BiH includes 154 municipalities, 12 thousands circles and 18 thousands enumeration areas. The sample frame for this survey was based on list of enumeration areas developed from the 1991 population census. In 2006 the update of 1500 enumeration areas was done and this master sample frame was used for sample selection.

The primary sampling unit (PSU), the cluster for the 2006 MICS, is defined on the basis of the enumeration areas from the master sample frame. A total of 455 census enumeration areas were systematically selected from the Master Sample with equal probability. All households from 455 census enumeration areas were allocated to two household lists. The first list (type 1) consisted of all households with children under five, and the second list consisted of all other households. 3,000 households having equal selection probability were selected from each list. This meant that each household from the list had the same selection probability. As the lists were different, the households with different sizes from different lists had different selection probability. Thus, a sample was obtained, which was self-weighted at the level of each list but is not self-weighted at the national level.

The number of households within each cluster is unequal and proportional to the cluster size.

The households in each list were implicitly stratified, i.e. sorted by entity/district, by urban/rural classification, by order of census enumeration area within the municipality, and by ordinal number within the cluster.

No replacement of households was permitted in case of non-response or non-contactable households. Adjustments were made to the sampling weights to correct for non-response, according to MICS standard procedures.

The sampling procedures are more fully described in the sampling design document and the sampling appendix of the final report.

Sampling deviation

No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the BiH MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household listing, education, water and sanitation, household characteristics,child labour, child discipline, child disability, household expenditure, and household incomes.

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

The women's questionnaire includes women's characteristics, marriage-union, contraception and unmet need, attitude toward domestic violence, sexual behavior, and HIV/AIDS knowledge.

The children's questionnaire includes children's characteristics, birth registration and early learning, child development, breastfeeding, care of illness, immunization, and anthropometry.

The questionnaires were developed in Bosnian, Serbian and Croatian from the MICS3 Model Questionnaires. After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey. The back translation from theBosnian, Serbian and Croatian versions was independently reviewed and compared to the English original. Differences in translation were reviewed and resolved in collaboration with the original translators.

The Bosnian, Serbian and Croatian questionnaires were both piloted as part of the survey pretest.

Cleaning operations

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

Detailed documentation of the editing of data can be found in the data processing guidelines

Response rate

At the BiH level (Table HH.1), 5,549 households were successfully interviewed and the response rate reached 93.4 percent. In the interviewed households, 4,977 women were identified within the sample range, out of which 4,890 were interviewed. A total of 3,209 children under five years-of-age were listed in the household questionnaire, and the questionnaire was completed for 3,188 children. The ratio of responses for children under five differed significantly between rural areas (89.0 percent) and other areas (95.2 percent).

In the Republika Srpska, 2,019, out of the 2,129

This is collection of DWR Region Land Use Surveys. These include several county land use surveys, In addition, you may scroll the list below to download any individual survey of interest. Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer. For Statewide Crop Mapping follow the link below : https://data.cnra.ca.gov/dataset/statewide-crop-mapping For County Land Use Surveys follow link below: https://data.cnra.ca.gov/dataset/resources/county-land-use-surveys Questions about the survey data may be directed to Landuse@water.ca.gov.

Abstract

China Living Standards Survey (LSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.

Geographic coverage

Regional

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The China LSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in North-eastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930's. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930's. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus, the intended sample size was 780 households, 130 from each county. Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list. In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households

Mode of data collection

Face-to-face [f2f]

Cleaning operations

(a) DATA ENTRY All responses obtained from the household interviews were recorded in the household questionnaires. These were then entered into the computer, in the field, using data entry programs written in BASIC. The data produced by the data entry program were in the form of household files, i.e. one data file for all of the data in one household/community questionnaire. Thus, for the household there were about 880 data files. These data files were processed at the University of Toronto and the World Bank to produce datasets in statistical software formats, each of which contained information for all households for a subset of variables. The subset of variables chosen corresponded to data entry screens, so these files are hereafter referred to as "screen files". For the household survey component 66 data files were created. Members of the survey team checked and corrected data by checking the questionnaires for original recorded information. We would like to emphasize that correction here refers to checking questionnaires, in case of errors in skip patterns, incorrect values, or outlying values, and changing values if and only if data in the computer were different from those in the questionnaires. The personnel in charge of data preparation were given specific instructions not to change data even if values in the questionnaires were clearly incorrect. We have no reason to believe that these instructions were not followed, and every reason to believe that the data resulting from these checks and corrections are accurate and of the highest quality possible.

(b) DATA EDITING The screen files were then brought to World Bank headquarters in Washington, D.C. and uploaded to a mainframe computer, where they were converted to "standard" LSMS formats by merging datasets to produce separate datasets for each section with variable names corresponding to the questionnaires. In some cases, this has meant a single dataset for a section, while in others it has meant retaining "screen" datasets with just the variable names changed. Linking Parts of the Household Survey Each household has a unique identification number which is contained in the variable HID. Values for this variable range from 10101 to 60520. The first number is the code for the six counties in which data were collected, the second and third digits are for the villages within each county. Finally, the last two digits of HID contain the household number within the village. Data for households from different parts of the survey can be merged by using the HID variable which appears in each dataset of the household survey. To link information for an individual use should be made of both the household identification number, HID, and the person identification number, PID. A child in the household can be linked to the parents, if the parents are household members, through the parents' id codes in Section 01B. For parents who are not in the household, information is collected on the parent's schooling, main occupation and whether he/she is currently alive. Household members can be linked with their non-resident children through the parents' id codes in Section 01C. Linking the Household to the Community Data The community data have a somewhat different set of identifying variables than the household data. Each community dataset has four identifying variables: province (code 7 for Hebei and code 8 for Liaoning); county (six two digit codes, of which the first digit represents province and the second digit represents the three counties in each province); township (3 digit code, first digit is county, second digit is county and third digit is township); and village (4 digit code, first digit is county, second digit is county, third digit is township, and third fourth digit is village). Constructed Data Set Researchers at the World Bank and the University of Toronto have created a data set with information on annual household expenditures, region codes, etc. This constructed data set is made available for general use with the understanding that the description below is the only documentation that will be provided. Any manipulation of the data requires assumptions to be made and, as much as possible, those assumptions are explained below. Except where noted, the data set has been created using only the original (raw) data sets. A researcher could construct a somewhat different data set by incorporating different assumptions. Aggregate Expenditure, TOTEXP. The dataset TOTEXP contains variables for total household annual expenditures (for the year 1994) and variables for the different components of total household expenditures: food expenditures, non-food expenditures, use value of consumer durables, etc. These, along with the algorithm used to calculate household expenditures are detailed in Appendix D. The dataset also contains the variable HID, which can be used to match this dataset to the household level data set. Note that all of the expenditure variables are totals for the household. That is, they are not in per capita terms. Researchers will have to divide these variables by household size to get per capita numbers. The household size variable is included in the data set.

The most important pieces of documentation for the Russia Longitudinal Monitoring Survey data sets are the questionnaires. The questionnaire files are English-language translations of the original Russian questionnaires. The English versions have been translated as literally as possible. The order of the questions and the layout of the pages have been preserved in the English versions. The questionnaires are also designed to function as codebooks. The variable names, as they appear in the data sets, are usually listed below or to the left of the questions. If the abbreviation (char) appears with a variable name, then the responses to that question are stored in a character variable. If there is no variable name associated with a particular question, then the responses to that question do not appear in the data set. Some questions in the questionnaires are color coded. Pink means that the question was added. Green indicates changes from the previous round (e.g., year). Gray means that the questions were asked, but the data are not available for public use - the questions were added at the request of the Pension Office and are for their use only. The original Russian-language questionnaires are available for all rounds, with the exception of the community questionnaires, which are only available for 2000-2003 and from 2011 on. Please note that, unlike the English-language versions, variable names do not appear in the Russian-language versions.