The General Social Surveys (GSS) have been conducted by the "https://www.norc.org/Pages/default.aspx" Target="_blank">National Opinion Research Center (NORC) annually since 1972 except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS is designed as part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. The 2006 GSS features special modules on mental health and social networks. Items on religion cover denominational affiliation, church attendance, religious upbringing, personal beliefs, and religious experiences.

To download syntax files for the GSS that reproduce well-known religious group recodes, including RELTRAD, please visit the "/research/syntax-repository-list" Target="_blank">ARDA's Syntax Repository.

Randomized list of General Social Survey triads for Interaction Priors Project being done in collaboration with Ryne Sherman. Starting from the top, we are pruning out all items which presuppose any particular answer to a prior question. For Third Element in each triad, we are pruning out demographic questions. We will work until we have 1000 triads that are valid by the criteria just stated.

Abstract

The 2022 Ghana Demographic and Health Survey (2022 GDHS) is the seventh in the series of DHS surveys conducted by the Ghana Statistical Service (GSS) in collaboration with the Ministry of Health/Ghana Health Service (MoH/GHS) and other stakeholders, with funding from the United States Agency for International Development (USAID) and other partners.

The primary objective of the 2022 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the GDHS collected information on: - Fertility levels and preferences, contraceptive use, antenatal and delivery care, maternal and child health, childhood mortality, childhood immunisation, breastfeeding and young child feeding practices, women’s dietary diversity, violence against women, gender, nutritional status of adults and children, awareness regarding HIV/AIDS and other sexually transmitted infections, tobacco use, and other indicators relevant for the Sustainable Development Goals - Haemoglobin levels of women and children - Prevalence of malaria parasitaemia (rapid diagnostic testing and thick slides for malaria parasitaemia in the field and microscopy in the lab) among children age 6–59 months - Use of treated mosquito nets - Use of antimalarial drugs for treatment of fever among children under age 5

The information collected through the 2022 GDHS is intended to assist policymakers and programme managers in designing and evaluating programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

To achieve the objectives of the 2022 GDHS, a stratified representative sample of 18,450 households was selected in 618 clusters, which resulted in 15,014 interviewed women age 15–49 and 7,044 interviewed men age 15–59 (in one of every two households selected).

The sampling frame used for the 2022 GDHS is the updated frame prepared by the GSS based on the 2021 Population and Housing Census.1 The sampling procedure used in the 2022 GDHS was stratified two-stage cluster sampling, designed to yield representative results at the national level, for urban and rural areas, and for each of the country’s 16 regions for most DHS indicators. In the first stage, 618 target clusters were selected from the sampling frame using a probability proportional to size strategy for urban and rural areas in each region. Then the number of targeted clusters were selected with equal probability systematic random sampling of the clusters selected in the first phase for urban and rural areas. In the second stage, after selection of the clusters, a household listing and map updating operation was carried out in all of the selected clusters to develop a list of households for each cluster. This list served as a sampling frame for selection of the household sample. The GSS organized a 5-day training course on listing procedures for listers and mappers with support from ICF. The listers and mappers were organized into 25 teams consisting of one lister and one mapper per team. The teams spent 2 months completing the listing operation. In addition to listing the households, the listers collected the geographical coordinates of each household using GPS dongles provided by ICF and in accordance with the instructions in the DHS listing manual. The household listing was carried out using tablet computers, with software provided by The DHS Program. A fixed number of 30 households in each cluster were randomly selected from the list for interviews.

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

Mode of data collection

Face-to-face computer-assisted interviews [capi]

Research instrument

Four questionnaires were used in the 2022 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Ghana. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

The GSS organized a questionnaire design workshop with support from ICF and obtained input from government and development partners expected to use the resulting data. The DHS Program optional modules on domestic violence, malaria, and social and behavior change communication were incorporated into the Woman’s Questionnaire. ICF provided technical assistance in adapting the modules to the questionnaires.

Cleaning operations

DHS staff installed all central office programmes, data structure checks, secondary editing, and field check tables from 17–20 October 2022. Central office training was implemented using the practice data to test the central office system and field check tables. Seven GSS staff members (four male and three female) were trained on the functionality of the central office menu, including accepting clusters from the field, data editing procedures, and producing reports to monitor fieldwork.

From 27 February to 17 March, DHS staff visited the Ghana Statistical Service office in Accra to work with the GSS central office staff on finishing the secondary editing and to clean and finalize all data received from the 618 clusters.

Response rate

A total of 18,540 households were selected for the GDHS sample, of which 18,065 were found to be occupied. Of the occupied households, 17,933 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,317 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,014 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 7,263 men age 15–59 were identified as eligible for individual interviews and 7,044 were successfully interviewed.

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 2022 Ghana Demographic and Health Survey (2022 GDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 GDHS 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 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% 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 2022 GDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the GDHS 2022 is an SAS program. This program used the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables

• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Standardisation exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women and men
• Heaping in anthropometric measurements for children (digit preference)
• Observation of mosquito nets
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Number of

Abstract (en): The Korean General Social Survey (KGSS) is the South Korean version of the General Social Survey (GSS), closely replicating the original GSS of the National Opinion Research Center at the University of Chicago. Each round of the KGSS typically includes the topical module of the International Social Survey Programme (ISSP), and/or the East Asian Social Survey (EASS), an international survey network of four GSS-type surveys from countries in East Asia (including China, Japan, Taiwan, and South Korea). In this data collection respondents were asked for their opinions on Korean society, crime, politics, economic issues, and social equity and inequality. Additional questions were asked about the household, family, education, financial situation, occupation, and everyday life of the respondents. Demographic and background variables include age, sex, marital status, education level, household composition, household income, employment status, religious preference, and political party affiliation. No weights were used in this study. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Response Rates: Approximately 60 percent All national populace aged 18 years and older residing in households in South Korea Smallest Geographic Unit: State Consistent with the requirements of ISSP and other GSS-type surveys, the sample for the KGSS is a national sample drawn by full probability sampling procedures. A more convenient quota sampling at the block level is not employed at all, simply because the quota sampling in terms of age and sex criteria, for instance, is vulnerable to a variety of misuses and abuses that result in serious sampling biases. The target universe of the KGSS is the adult population aged 18 or over who live in households of Korea. From this universe, a total of 2,000 individuals are sampled by the three-stage area probability sampling method. The total number of sample blocks (or clusters) is 200, and some 10 individuals are sampled from each block. Below is a more detailed description of the sampling procedures involved. First, the total sample blocks are distributed to 16 do's or si's at the province level, proportionate to the distribution of households in Korea. Second, in accordance with the PPS principle, a number of dong's and/or myun's (ward level administrative districts in cities and rural counties, respectively) are selected proportional to the number of sample blocks assigned to each province. Third, from each dong and myun selected, one sample block-tong-ban in dong or ri inmyun-is randomly selected. Fourth, in each tong-ban or ri selected, about 10 households are randomly selected, make a list of adult members aged 18 or over in each household with their dates of birth on it, and finally select the person who has the birth date occurring the first during the year. For instance, in a household whose members have birthdays in April, February, November, and August, the very person with the birthday in February becomes the respondent. The multistage element in these sequential sampling procedures serves to narrow down the hierarchically stratified geographic areas into the lowest sample blocks, thereby enhancing the sample representativeness, while the cluster component there serves to maximize the efficiency of fieldwork operations. face-to-face interview More information about Korean General Social surveys can be found on the Korean General Social Survey Web site (Korean language) or the Korean General Social Survey Web site (English language).

Abstract

The Ghana Statistical Service (GSS) and the World Bank Development Economics Research Group (DECRG) partnered to implement the survey. The purpose was to find out household's access to and use of available financial services.This was a follow-up to an earlier test of survey designs regarding household access to financial services. The underlying premise is that the identity of a respondent can affect the quality and completeness of the information provided, especially when that respondent is providing information about other household members.

The survey will examine whether questions about specific products (e.g. credit cards, life insurance policies, savings clubs) elicit more complete information than questions asking whether a respondent uses services from a type of provider (e.g. commercial bank, credit union).

To derive the data necessary for these tests, the Financial Service Survey incorporated an experimental design in which one of three versions of the survey instrument (questionnaire) was randomly administered to each household. Individual household members were also randomly selected to respond to some sections of the questionnaire.

Geographic coverage

National Regional District, Municipal, Metropolitan

Analysis unit

Individuals

Universe

The survey covered all adult household members (usual residents) aged 15 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The most recently visited enumeration areas (EAs) for the Ghana Living Standards Survey Round 5 (GLSS5) were targeted for the survey. This is because the characteristics of these households may not have changed much, and they were more likely to recollect information they had already provided. All the 120 EAs visited in the 10th and 11th cycles of the GLSS5 were included in the survey, with an additional 34 EAs selected from the 60 EAs visited in the 9th cycle. Households within the 154 EAs were listed and 15 selected randomly from each EA yielding a total of 2,310 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey:

1. Group 1 Questionnaire - All questions in the three (3) sections were administered to all household members aged 15 years and older. It collected information on background characteristics, the use of financial services and products and actions and attitudes towards accessing and using financial services and products.

2. Group 2 Questionnaire - Sections 1 and 2 of this questionnaire were administered to all household members aged 15 years and older. Sections 3 and 4 were administered to household members randomly selected using the Kish Grid based on given criteria.

3. Group 3 Questionnaire - All questions in section (1) were administered to heads of household and one randomly selected household member and covered background characteristics. Section two (2) was administered to heads of household and covered the use of financial services. Sections 3 and 4 were administered to a randomly selected household member and covered the use of financial services and products and actions and attitudes towards access and use of financial services and products.

All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. An interpreter was also used where the interviewer was not proficient in the respondent's choice of language.

Cleaning operations

The GSS data editing occurs at three levels:

1. Field editing by interviewers and supervisors
2. Office editing
3. Data cleaning and imputation

Response rate

Out of the 2,310 households selected for the survey, 2,292 were identified and successfully enumerated. This yielded a response rate of 99.2 percent.

The National Congregations Study (NCS) dataset "fills a void in the sociological study of congregations by providing, for the first time, data that can be used to draw a nationally aggregate picture of congregations" (Chaves et al. 1999, p.460). Thanks to innovations in sampling techniques, the NCS data is the first nationally representative sample of American congregations. In 2006-07, a panel component was added to the NCS. In addition to the new cross-section of congregations generated in conjunction with the 2006 General Social Survey (GSS), a stratified random sample was drawn from congregations who participated in the 1998 NCS. A full codebook, prepared by the primary investigator, is available for download "https://sites.duke.edu/ncsweb/" Target="_blank">here. The codebook contains the original questionnaire, as well as detailed information on survey methodology, weights, coding, and more.

Variable names have been shortened to allow for downloading of the data set as an SPSS portable file. Original variable names are shown in parentheses at the beginning of each variable description.

The "/data-archive?fid=NCSIV" Target="_blank">NCS Cumulative Dataset is also available from the ARDA.

Database of unannotated short single-read primarily genomic sequences from GenBank including random survey sequences clone-end sequences and exon-trapped sequences. The GSS division of GenBank is similar to the EST division, with the exception that most of the sequences are genomic in origin, rather than cDNA (mRNA). It should be noted that two classes (exon trapped products and gene trapped products) may be derived via a cDNA intermediate. Care should be taken when analyzing sequences from either of these classes, as a splicing event could have occurred and the sequence represented in the record may be interrupted when compared to genomic sequence. The GSS division contains (but is not limited to) the following types of data: * random single pass read genome survey sequences. * cosmid/BAC/YAC end sequences * exon trapped genomic sequences * Alu PCR sequences * transposon-tagged sequences Although dbGSS sequences are incorporated into the GSS Division of GenBank, annotation in dbGSS is more comprehensive and includes detailed information about the contributors, experimental conditions, and genetic map locations.

The General Social Survey (GSS) gathers data on social trends in order to monitor changes in the living conditions and well-being of Canadians over time, and to provide immediate information on specific social policy issues of current or emerging interest. This survey monitors changes in time use to better understand how Canadians spend and manage their time and what contributes to their well-being and stress. The data collected provides information to all level of governments when making funding decisions, developing priorities and identifying areas of concern for legislation, new policies and programs. Researchers and other users use this information to inform the general Canadian population about the changing nature of time use in Canada such as: o Are we working too many hours and spending too much time commuting? o Do we have flexible work schedules? o Do we have enough time to play sports, participate in leisure activities or volunteer? o Are we spending enough quality time with our children, our families and our friends? o How has the internet and social media affected the way we spend our time? o Are we satisfied with our lives? New elements were introduced to the GSS cycle for 2015. First, the survey frame has changed. Previous GSS cycles on Time Use were conducted as Random Digit Dialling (RDD) surveys and did not include cellular numbers. In 2015,the survey was implemented using the redesigned GSS frame created in 2013, which integrates data from sources of telephone numbers (landline and cellular) available to Statistics Canada and the Address Register (AR). Second, there is a new weighting strategy and bootstrap weights have also been changed from mean bootstrap to standard bootstrap weights.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries. The survey covered 20 countries in Round 4 (2008-2009).

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 1200 Sampling frame: 2008 projected population provided by the Ghana Statistical Service (GSS) based on the GSS’s 2000 Population and Housing Census. Sample universe: Citizens age 18 years or older, excluding institutions Sample design: Nationally representative, random, clustered, stratified, multistage area probability sample. Stratification: Region and urban-rural location Stages: PSUs (from strata), households, respondents PSU selection: Probability proportionate to population size (PPPS) Cluster size: 8 households per PSU Household selection: Randomly done from GSS household list prior to fieldwork. Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which household member draws a numbered card to select individual.

Mode of data collection

Face-to-face [f2f]

Response rate

Response rate of the survey was 90.2%.

Data appraisal

Margin of error: +/- 3% with 95% confidence level.

Many dinoflagellate species are notorious for the toxins they produce and ecological and human health consequences associated with harmful algal blooms (HABs). Dinoflagellates are particularly refractory to genomic analysis due to the enormous genome size, lack of knowledge about their DNA composition and structure, and peculiarities of gene regulation, such as spliced leader (SL) trans-splicing and mRNA transposition mechanisms. Alexandrium ostenfeldii is known to produce macrocyclic imine toxins, described as spirolides. We characterized the genome of A. ostenfeldii using a combination of transcriptomic data and random genomic clones for comparison with other dinoflagellates, particularly Alexandrium species. Examination of SL sequences revealed similar features as in other dinoflagellates, including Alexandrium species. SL sequences in decay indicate frequent retro-transposition of mRNA species. This probably contributes to overall genome complexity by generating additional gene copies. Sequencing of several thousand fosmid and bacterial artificial chromosome (BAC) ends yielded a wealth of simple repeats and tandemly repeated longer sequence stretches which we estimated to comprise more than half of the whole genome. Surprisingly, the repeats comprise a very limited set of 79–97 bp sequences; in part the genome is thus a relatively uniform sequence space interrupted by coding sequences. Our genomic sequence survey (GSS) represents the largest genomic data set of a dinoflagellate to date. Alexandrium ostenfeldii is a typical dinoflagellate with respect to its transcriptome and mRNA transposition but demonstrates Alexandrium-like stop codon usage. The large portion of repetitive sequences and the organization within the genome is in agreement with several other studies on dinoflagellates using different approaches. It remains to be determined whether this unusual composition is directly correlated to the exceptionally genome organization of dinoflagellates with a low amount of histones and histone-like proteins.

Digitization of a selection of oil and gas well pad sites in the Piceance region of Western Colorado. A random sample of 146 pad locations from the "Digitized Piceance Oil and Gas Pads of Western Colorado, 2015" were used to identify the locations digitized in this dataset. The 146 polygons spatially intersect polygons in the 2015 shape file, but are not completely contained within the 2015 polygons. Well pad sites were delineated using a modified version of the Rapid Land Cover Mapping protocol (Preston and Kim, 2016). The base imagery used to delineate boundaries is the 2005 National Agriculture Imagery Program (NAIP) imagery.

Abstract

The data is created from two firm censuses, both conducted by the Ghana Statistical Service. These were the 2003 NIC and the 2014 IBES. Identifying information on these firms such as firm name, firm locations, contact person, contact number etc were sourced from GSS for IBES 2014 and from Francis Teal for NIC 2003. This information was used to match firms over the 2 waves. The creation of the panel was funded by the Project for Enterprise Development in Low Income Countries (PEDL) and was undertaken by Andrew Kerr and Bruce McDougall of DataFirst, University of Cape Town

Geographic coverage

This panel is a handful of firms we found that were interviewed in both 2003 and 2014 - it is not geographically representative.

Analysis unit

Establishments

Universe

Establishments in Ghana.

Sampling procedure

This dataset is a panel derived from matching firms that were included in two Ghanaian censuses, NIC 2003 and IBES 2014. Each of these censuses had two phases.

2014 IBES Phase 1 was a census of non-household establishments with a fixed site and any household-based business with a sign indicating its presence within a household. Phase 2 was a stratified roughly 5% sample of the phase 1 firms. NIC 2003 Phase 1 was a census of non-household establishments with a fixed site and any household-based business with a sign indicating its presence within a household. Phase 2 was a stratified sample. All establishments with 10 or more persons engaged were enumerated and 5% firms with less than 10 persons engaged were sampled for phase 2. The phase 1 data was used to match firms across 2003 NIC and 2014 IBES and create the panel. This matching is likely to be non-random and a function of observable and unobservable characteristics. Thus the panel SHOULD NOT be considered a random sample of establishments alive in both 2003 and 2014.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

A detailed guide on how the NIC and IBES firms were matched using fuzzy algorithms has been uploaded for the users reference.

Data appraisal

The main data quality issue that users should be aware of is that these firms were matched using fuzzy logic - not all the matches are strong matches and some might be false matches.

Abstract

The Ghana Living Standards Survey (GLSS), with its focus on the household as a key social and economic unit, provides valuable insights into living conditions in Ghana. The survey was carried out by the Ghana Statistical Service (GSS) over a 12-month period (April 1998 to March 1999). A representative nationwide sample of more than 5,998 households, containing over 25,000 persons, was covered in GLSS IV.

The fourth round of the GLSS has the following objectives: · To provide information on patterns of household consumption and expenditure disaggregated at greater levels. · In combination with the data from the earlier rounds to serve as a database for national and regional planning. · To provide in-depth information on the structure and composition of the wages and conditions of work of the labor force in the country. · To provide benchmark data for compilation of current statistics on average earnings, hours of work and time rates of wages and salaries that will indicate wage/salary differentials between industries, occupations, geographic locations and gender.

Additionally, the survey will enable policy-makers to · Identify vulnerable groups for government assistance; · Analyze the impact of decisions that have already been implemented and of the economic situation on living conditions of households; · Monitor and evaluate the employment policies and programs, income generating and maintenance schemes, vocational training and similar programs. The joint measure of employment, income and expenditure provides the basis for analyzing the adequacy of employment of different categories of workers and income-generating capacity of employment-related economic development.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community
• Commodity

Kind of data

Sample survey data [ssd]

Sampling procedure

A nationally representative sample of households was selected in order to achieve the survey objectives. For the purposes of this survey the list of the 1984 population census Enumeration Areas (EAs) with population and household information was used as the sampling frame. The primary sampling units were the 1984 EAs with the secondary units being the households in the EAs. This frame, though quite old, was considered the best available at the time. Indeed, this frame was used for the earlier rounds of the GLSS.

In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.

A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected. It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households. At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labor force focus of the survey.

NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because: - given the long period between 1984 and the GLSS 4 fieldwork the number of households in the various EAs are likely to have grown at different rates. - The listing exercise was not properly done as some of the selected EAs were not listed completely. Moreover, it was noted that the segmentation done for larger EAs during the listing was a bit arbitrary.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main questionnaire used in the survey was the household questionnaire. In addition to this, there were community and Price questionnaires.

• Household Questionnaire: The household questionnaire was used to collect information on various topics some of which pertain to eligible individual household members. The questionnaire is in two parts, A and B.
• Community Questionnaire: The main aim of the community questionnaire was is to identify the economic infrastructure, education and health facilities existing in the villages, as well as any related problems that affects their welfare. The questionnaire was administered in the rural EAs only.
• Price Questionnaire: As part of the survey a price questionnaire was designed to collect prices of most essential commodities in the local markets.

Cleaning operations

Training: The project had 3 experienced computer programmers responsible for the data processing. Data processing started with a 2-weeks training of 15 data entry operators out of which the best 10 were chosen and 2 identified as standby. The training took place one week after the commencement of the fieldwork.

Data entry: Each data entry operator was assigned to one field team and stationed in the regional office of the GSS. The main data entry software used to capture the data was IMPS (Integrated Microcomputer Processing System). The data capture run concurrently as the data collection and lasted for 12 months.

Tabulation/Analysis: The IMPS data was read into SAS (Statistical Analysis System), after which the analysis and generation of the statistical tables were done using SAS.

Response rate

Out of the selected 6000 households 5999 were successfully interviewed. One household was further dropped during the data cleaning exercise because it had very few records for many of the sections in the questionnaire. This gave 5998 household representing 99.7% coverage. Overall, 25,694 eligible household members (unweighted) were covered in the survey.

Abstract

Introduction The Multiple Indicator Cluster Survey (MICS) 2006 is a national sample survey designed to provide information on population, maternal and child health, child survival, reproductive health, nutrition, AIDS and sexually transmitted infections (STIs) in Ghana. MICS 2006 has different target population and involved interviewing a randomly selected group of men and women who are between 15 and 49 years of age. The women were asked questions about their background, the children they have given birth to, their knowledge and use of family planning methods, the health of their children, reproductive health, and other information that are helpful to policy makers and administrators in health and family planning fields. The men were asked questions about their background, the children they have fathered, their marriage status and sexual behaviour, and other information which were helpful to policymakers and administrators in health fields.

The questionnaires are based on the MICS model questionnaires and modified to fit the Ghanaian survey standards and conditions. The questionnaires were pre-tested in the Greater Accra Region in June 2006. The training for the pre-test was conducted by GSS staff for 22 interviewers for 13 days. This was followed by the formation of four teams consisting of a supervisor and four interviewers that conducted the pilot survey in four selected localities (2 urban and 2 rural) in the same region to test the entirety of survey procedures. Based on the results of the pre-test and pilot, further modifications were made to wording and flow of the questions and the survey plan. A copy of MICS 2006 questionnaires is provided in Appendix F.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine level, and measured the heights and weights of all children less than 5 years (0-59 months).

Survey objectives The MICS is part of a worldwide survey program, originally developed to measure progress towards an internationally agreed set of goals that emerged from the 1990 World Summit for Children. The MICS 2006 has the following primary objectives:

§ To provide up-to-date information for assessing the health situation of women and children in Ghana; § To present the current level of knowledge and behavioural indicators regarding HIV/AIDS and malaria; § To furnish data needed for monitoring progress toward the Millennium Development Goals, and the goals of A World Fit for Children (WFFC) as a basis for future action; such as the US President's Emergency Plan for AIDS Relief (PEPFAR). § To contribute to the formation of baselines for the GPRS II and the Ministry of Health (MoH) Plan of Work 2007-2011, and to provide progress monitoring for other policies and programmes in Ghana; § To contribute to the improvement of data and monitoring systems in Ghana and to strengthen technical expertise in the design, implementation, and analysis of such systems.

This report is based on the Ghana Multiple Indicator Cluster Survey, conducted in 2006 by Ghana Statistical Service and the Ministry of Health. The survey provides valuable information on the situation of women, men and children in Ghana. It was based largely on the need to monitor progress towards goals and targets emanating from recent international agreements, the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000 and the Plan of Action of A World Fit for Children, adopted by 189 Member States at the United Nations Special Session on Children in May 2002.

Content Four sets of questionnaires were used in the survey to solicit the appropriate responses: § ·household questionnaire which was used to collect information on all de jure household members, and dwelling, and household characteristics and to identify eligible individuals; § ·women's questionnaire administered in each household to all women aged 15-49 years; § men's questionnaire administered in every third selected household to all men aged 15-49 years; § ·under-5 questionnaire, administered to mothers or caretakers of all children under five years living in the household.

The questionnaires included the following modules: § Household Questionnaire: § Household Listing § Education § Water and Sanitation § Durability of Housing § Malaria-related questions § Child Labour § Child Discipline § Disability § Salt Iodization

Women Questionnaire: § Child Mortality § Tetanus Toxoid § Maternal and Newborn Health § Marriage and Union § Security of Tenure § Contraception § Attitudes towards Domestic Violence § Female Genital Mutilation/Cutting § Sexual Behaviour § HIV knowledge Men Questionnaire: § Marriage and Union § Sexual Behaviour § Contraception § HIV/AIDS and other Sexually Transmitted Infections (STIs) Under-five Questionnaire: § Birth Registration and Early Learning § Child Development § Vitamin A § Breastfeeding § Care of Illness § Malaria § Immunization § Anthropometry

Geographic coverage

National Regional

Analysis unit

Individuals

Universe

1. All women age 15-49 years
2. All men age 15-49 years
3. All children under 5 years
4. All househld members

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design

The sample for the MICS 2006 was designed to provide estimates on a large number of indicators of the health status of women, men, and children at the national level, for urban and rural areas, as well as for the 10 administrative regions in the country. A representative probability sample of 6,302 households was selected nationwide. The list of enumeration areas (EAs) from the Ghana Living Standards Survey 5 (GLSS5) served as a frame for the MICS sample. The frame was first stratified into the 10 administrative regions in the country, then into urban and rural EAs. 660 EAs {-281 urban and 379 rural}

1) Twenty households per EA were selected 2) 25 per EA for rural EAs in Northern, Upper East and Upper West. 3) All women aged 15-49 and children less than 60 months in these selected households were eligible for interview. 4) Males in every selected third household aged 15-49 were also eligible for interview. 5) This is different from DHS whereby males aged 15-59 are eligible for interview.

The MICS 2006 used a two-stage stratified sample design. At the first stage of sampling, 300 census enumeration areas (124 urban and 176 rural EAs) were selected. These are a sub-sample of the 660 EAs (281 urban and 379 rural) selected for the GLSS 5 and fisheries. The clusters in each region were selected using systematic sampling with probability proportional to their size. The distribution of EAs between regions is not proportional to the 2000 Population and Housing Census, mainly due to over-sampling in the number of EAs for Northern, Upper East and Upper West Regions.

A complete household listing exercise covering all the GLSS 5 EAs was carried out in May through July 2005 with a few selected EAs listed early 2006. At the second stage, a systematic sampling of households was selected based on this list. The MICS households were selected systematically from the household listing provided by GLSS 5 after eliminating from the list households previously selected by the GLSS 5 (15 regular with 5 replacement). The reason for selecting different households is that the GLSS 5 interviews are long and demanding for respondents. It therefore seemed preferable to keep the two household samples separate in order to avoid respondent fatigue and possible high rates of refusal in the households falling in both samples as they were being conducted concurrently. For the MICS, 20 households per EA were selected in all the regions except in Northern, Upper East and Upper West regions, where 20 households per EA were selected in urban EAs and 25 households selected from rural EAs. The objective of this exercise was to ensure an adequate number of complete interviews to provide estimates for important population characteristics with acceptable statistical precision per region. Due to the disproportional number of EAs and different sample sizes selected per EA among regions, the MICS 2006 household sample is not self-weighting at the national level. For reporting national level results, sample weights are used. A more detailed description of the sample design can be found in Appendix A.

Sample Size and Sample Allocation

The sample size for MICS 2006 was calculated as 6,300 households using basically the same sample of clusters selected for DHS 2003, as well as for similar sample size. The resulting number of households from this exercise was a minimum of about 500 (except for Upper West Region) households which is the sample size needed in each region - thus yielding about 6,500 in total. The average cluster size in MICS 2006 was determined as 20 households (except in rural clusters in Northern, Upper East and Upper West Regions with 25 households) based on a number of considerations, including the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of households per cluster, it was calculated that the selection of a minimum of about 25 clusters would be needed in each region.

The allocation of the total sample size to each of the ten regions follows almost same allocation than the DHS 2003. Therefore, a minimum of 25 clusters were allocated to each region, with the final sample size calculated at 6,300 households and 300 clusters in total. In each region, the clusters (primary sampling units) were distributed to urban and rural domains, proportional to the size of urban and rural populations in that region. The

Abstract

The Ghana Demographic and Health Survey (GDHS) is a national sample survey designed to provide information on fertility, family planning and health in Ghana. The survey, which was conducted by the Statistical Service of Ghana, is part of a worldwide programme coordinated by the Institute for Resource Development/Macro Systems, Inc., in more than 40 countries in Africa, Asia and Latin America.

The short-term objectives of the Ghana Demographic and Health Survey (GDHS) are to provide policymakers and those implementing policy with current data on fertility levels, knowledge and use of contraception, reproductive intentions of women 15-49, and health indicators. The information will also serve as the basis for monitoring and evaluating programmes initiated by the government such as the extended programme on immunization, child nutrition, and the family planning programme. The long-term objectives are to enhance the country's ability to undertake surveys of excellent technical quality that seek to measure changes in fertility levels, health status (particularly of children), and the extent of contraceptive knowledge and use. Finally, the results of the survey will form part of an international data base for researchers investigating topics related to the above issues.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

The 150 clusters from which a representative sample of women aged 15-49 was selected from a subsample of the 200 clusters used for the Ghana Living Standards Survey (GLSS). All census Enumeration Areas (EAs) were first stratified by ecological zones into 3 strata, namely Coastal Savanna, Forest, and Northern Savanna. These were further stratified into urban, semi-urban, and rural EAs. The EAs (in some cases, segments of EAs) were then selected with probability proportional to the number of households. All households in the selected EAs were subsequently listed.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face

Research instrument

Three different types of questionnaires were used for the GDHS. These were the household, individual and the husband questionnaires. The household and the individual questionnaires were adapted from the Model "B" Questionnaire for the DHS program. The GDHS is one of the few surveys in which special effort was made to collect information from husbands of interviewed women on such topics as fertility preferences, knowledge and use of contraception, and environmental and health related issues.

All usual members and visitors in the selected households were listed on the household questionnaire. Recorded in the household questionnaire were data on the age and sex of all listed persons in addition to information on fostering for children aged 0-14. Eligible women and eligible husbands were also identified in the household questionnaire.

The individual questionnaire was used to collect data on eligible women. Eligible women were definedas those aged 15-49 years who spent the night prior to the household interview in the selected household, irrespective of whether they were usual members of the household or not. Items of information collected in this questionnaire are as follows: 1) Respondent's Background 2) Reproductive Behavior 3) Knowledge and Use of Contraception 4) Health and Breastfeeding 5) Marriage 6) Fertility Preferences 7) Husband's Background and Women's Work 8) Weight and Height of Children Aged 3-36 Months.

In half of the selected clusters a husband's questionnaire was used to collect data on eligible husbands. Eligible husbands were defined as those who were co-resident with their wives and whose wives had been successfully interviewed. Data on the husband's background, contraceptive knowledge and use, as well as fertility preferences were collected.

All three questionnaires were translated into seven local languages, namely, Twi, Fante, Nzema, Ga, Ewe, Hausa and Dagbani. All the GDHS interviewers were able to conduct interviews in English and at least one local language. The questionnaires were pretested from mid-October to early November 1987. Five teams were used for the pretest fieldwork. These included 19 persons who were trained for 11 days.

Cleaning operations

Completed questionnaires were collected weekly from the regions by the field coordinators. Coding, data entry and machine editing went on concurrently at the Ghana Statistical Service in Accra as the fieldwork progressed. Coding and data entry were started in March 1988 and were completed by the end of June 1988. Preliminary tabulations were produced by mid-July 1988, and by August 1988 preliminary results of the survey were published.

Response rate

Of the 4966 households selected, 4406 were successfully interviewed. Excluding 9 percent of households that were vacant, absent, etc., the household response rate is 98 percent.

Out of 4574 eligible women in the household schedule, 4488 were interviewed successfully. The response rate at the individual level is 98 percent. Of the 997 eligible husbands, 943 were successfully interviewed, representing a response rate of 95 percent.

Sampling error estimates

The results from sample surveys are affected by two types of errors: non-sampling error and sampling error. The former is due to mistakes in implementing the field activities, such as failing to locate and interview the correct household, errors in asking questions, data entry errors, etc. While numerous steps were taken to minimize this sort of error in the GDHS, non-sampling errors are impossible to avoid entirely, and are difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of women selected in the GDHS is only one of many samples of the same size that could have been drawn from the population using the same design. Each sample would have yielded slightly different results from the sample actually selected. The variability observed among all possible samples constitutes sampling error, which can be estimated from survey results (though not measured exactly).

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

If simple random sampling had been used to select women for the GDHS, it would have been possible to use straightforward formulas for calculating sampling errors. However, the GDHS sample design used three stages and clusters of households, and it was necessary to use more complex formulas. Therefore, the computer package CLUSTERS, developed for the World Fertility Survey, and was used to compute sampling errors.

Note: See detailed estimate of sampling error calculation in APPENDIX C of the survey report.

Abstract

The 1998 Ghana Demographic and Health Survey (GDHS) is the latest in a series of national-level population and health surveys conducted in Ghana and it is part of the worldwide MEASURE DHS+ Project, designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 1998 GDHS is to provide current and reliable data on fertility and family planning behaviour, child mortality, children’s nutritional status, and the utilisation of maternal and child health services in Ghana. Additional data on knowledge of HIV/AIDS are also provided. This information is essential for informed policy decisions, planning and monitoring and evaluation of programmes at both the national and local government levels.

The long-term objectives of the survey include strengthening the technical capacity of the Ghana Statistical Service (GSS) to plan, conduct, process, and analyse the results of complex national sample surveys. Moreover, the 1998 GDHS provides comparable data for long-term trend analyses within Ghana, since it is the third in a series of demographic and health surveys implemented by the same organisation, using similar data collection procedures. The GDHS also contributes to the ever-growing international database on demographic and health-related variables.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

The major focus of the 1998 GDHS was to provide updated estimates of important population and health indicators including fertility and mortality rates for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of key variables for the ten regions in the country.

The list of Enumeration Areas (EAs) with population and household information from the 1984 Population Census was used as the sampling frame for the survey. The 1998 GDHS is based on a two-stage stratified nationally representative sample of households. At the first stage of sampling, 400 EAs were selected using systematic sampling with probability proportional to size (PPS-Method). The selected EAs comprised 138 in the urban areas and 262 in the rural areas. A complete household listing operation was then carried out in all the selected EAs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, a systematic sample of 15 households per EA was selected in all regions, except in the Northern, Upper West and Upper East Regions. In order to obtain adequate numbers of households to provide reliable estimates of key demographic and health variables in these three regions, the number of households in each selected EA in the Northern, Upper West and Upper East regions was increased to 20. The sample was weighted to adjust for over sampling in the three northern regions (Northern, Upper East and Upper West), in relation to the other regions. Sample weights were used to compensate for the unequal probability of selection between geographically defined strata.

The survey was designed to obtain completed interviews of 4,500 women age 15-49. In addition, all males age 15-59 in every third selected household were interviewed, to obtain a target of 1,500 men. In order to take cognisance of non-response, a total of 6,375 households nation-wide were selected.

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

Mode of data collection

Face-to-face

Research instrument

Three types of questionnaires were used in the GDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were based on model survey instruments developed for the international MEASURE DHS+ programme and were designed to provide information needed by health and family planning programme managers and policy makers. The questionnaires were adapted to the situation in Ghana and a number of questions pertaining to on-going health and family planning programmes were added. These questionnaires were developed in English and translated into five major local languages (Akan, Ga, Ewe, Hausa, and Dagbani).

The Household Questionnaire was used to enumerate all usual members and visitors in a selected household and to collect information on the socio-economic status of the household. The first part of the Household Questionnaire collected information on the relationship to the household head, residence, sex, age, marital status, and education of each usual resident or visitor. This information was used to identify women and men who were eligible for the individual interview. For this purpose, all women age 15-49, and all men age 15-59 in every third household, whether usual residents of a selected household or visitors who slept in a selected household the night before the interview, were deemed eligible and interviewed. The Household Questionnaire also provides basic demographic data for Ghanaian households. The second part of the Household Questionnaire contained questions on the dwelling unit, such as the number of rooms, the flooring material, the source of water and the type of toilet facilities, and on the ownership of a variety of consumer goods.

The Women’s Questionnaire was used to collect information on the following topics: respondent’s background characteristics, reproductive history, contraceptive knowledge and use, antenatal, delivery and postnatal care, infant feeding practices, child immunisation and health, marriage, fertility preferences and attitudes about family planning, husband’s background characteristics, women’s work, knowledge of HIV/AIDS and STDs, as well as anthropometric measurements of children and mothers.

The Men’s Questionnaire collected information on respondent’s background characteristics, reproduction, contraceptive knowledge and use, marriage, fertility preferences and attitudes about family planning, as well as knowledge of HIV/AIDS and STDs.

Response rate

A total of 6,375 households were selected for the GDHS sample. Of these, 6,055 were occupied. Interviews were completed for 6,003 households, which represent 99 percent of the occupied households. A total of 4,970 eligible women from these households and 1,596 eligible men from every third household were identified for the individual interviews. Interviews were successfully completed for 4,843 women or 97 percent and 1,546 men or 97 percent. The principal reason for nonresponse among individual women and men was the failure of interviewers to find them at home despite repeated callbacks.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of shortfalls made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 1998 GDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1998 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1998 GDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1998 GDHS is the ISSA Sampling Error Module. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

Abstract

The 2017 Ghana Maternal Health Survey (2017 GMHS) was designed to produce representative estimates for maternal mortality indicators for the country as a whole, and for each of the three geographical zones, namely Coastal (Western, Central, Greater Accra and Volta), Middle (Eastern, Ashanti and Brong Ahafo) and Northern (Northern, Upper East and Upper West). For other indicators such as maternal care, fertility and child mortality, the survey was designed to produce representative results for the country as whole, for the urban and rural areas, and for each of the country’s 10 administrative regions.

The primary objectives of the 2017 GMHS were as follows: • To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole and for three zones: Coastal (Western, Central, Greater Accra, and Volta regions), Middle (Eastern, Ashanti, and Brong Ahafo regions), and Northern (Northern, Upper East, and Upper West regions) • To identify specific causes of maternal and non-maternal deaths, in particular deaths due to abortionrelated causes, among adult women • To collect data on women’s perceptions of and experiences with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and following the termination or abortion of a pregnancy • To measure indicators of the utilisation of maternal health services, especially post-abortion care services • To allow follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as abortion-related mortality

The information collected through the 2017 GMHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Woman age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2017 GMHS was designed to provide estimates of key reproductive health indicators for the country as a whole, for urban and rural areas separately, for three zonal levels (Coastal, Middle, and Northern), and for each of the 10 administrative regions in Ghana (Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West).

The sampling frame used for the 2017 GMHS is the frame of the 2010 Population and Housing Census (PHC) conducted in Ghana. The 2010 PHC frame is maintained by GSS and updated periodically as new information is received from various surveys. The frame is a complete list of all census enumeration areas (EAs) created for the PHC.

The 2017 GMHS sample was stratified and selected from the sampling frame in two stages. Each region was separated into urban and rural areas; this yielded 20 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before the sample selection, according to administrative units at different levels, and by using a probability proportional to size selection at the first stage of sampling.

In the first stage, 900 EAs (466 EAs in urban areas and 434 EAs in rural areas) were selected with probability proportional to EA size and with independent selection in each sampling stratum. A household listing operation was implemented from 25 January to 9 April 2017 in all of the selected EAs. The resulting lists of households then served as a sampling frame for the selection of households in the second stage. The household listing operation included inquiring of each household if there had been any deaths in that household since January 2012 and, if so, the name, sex, and age at time of death of the deceased person(s).

Some of the selected EAs were very large. To minimise the task of household listing, each large EA selected for the 2017 GMHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment. Thus, in the GMHS, a cluster is either an EA or a segment of an EA. As part of the listing, the field teams updated the necessary maps and recorded the geographic coordinates of each cluster. The listing was conducted by 20 teams that included a supervisor, three listers/mappers, and a driver.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the 2017 GMHS: the Household Questionnaire, the Woman’s Questionnaire, and the Verbal Autopsy Questionnaire.

Cleaning operations

All electronic data files for the 2017 GMHS were transferred via the IFSS to the GSS central office in Accra, where they were stored on a password-protected computer. The data processing operation included registering and checking for any inconsistencies and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of openended questions. The data were processed by five GSS staff members. Data editing was accomplished using CSPro software. Secondary editing and data processing were initiated in June and completed in November 2017.

Response rate

A total of 27,001 households were selected for the sample, of which 26,500 were occupied at the time of fieldwork. Of the occupied households, 26,324 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 25,304 eligible women were identified for individual interviews; interviews were completed with 25,062 women, yielding a response rate of 99%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017 Ghana Maternal Health Survey (2017 GMHS) 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 2017 GMHS is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 GMHS sample is the result of a multi-stage stratified sampling, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF International. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Completeness of information on siblings - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends

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

Abstract

The survey was conducted in Ghana between December 2012 and July 2014 as part of the Africa Enterprise Survey 2013 roll-out, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Data from 720 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Ghana was selected using stratified random sampling. Three levels of stratification were used in this country: firm sector, firm size, and geographic region.

Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).

Size stratification was defined following the standardized definition for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

Regional stratification for the Ghana ES was defined in four regions: Accra, North (Kumasi and Tamale), Takoradi, and Tema.

For the Ghana ES, several sample frames were used. The first was supplied by the World Bank and consists of enterprises interviewed in Ghana 2007. The World Bank required that attempts should be made to re-interview establishments responding to the Ghana 2007 survey where they were within the selected geographical regions and met eligibility criteria. Due to the fact that the previous round of surveys seemed to have utilized different stratification criteria (or no stratification at all) and due to the prevalence of small firms and firms located in the capital city in the 2007 sample the following convention was used. The presence of panel firms was limited to a maximum of 50% of the achieved interviews in each cell. That sample is referred to as the Panel.

The second frame was constructed using different lists acquired from relevant institutions in Ghana. The main lists used were obtained from the Ghana Statistical Service (GSS). These include: 1) The 2012 Firm Registry. The registry lacked information on firm employee size. 2) The list of firms paying VAT. The VAT dataset included a variable on firms; turnover. The VAT dataset and Firm Registry were merged by using the firms' identification number (TIN). VAT information was not available for all firms in the Firm Registry. 3) The list of Large Tax Payers. The Large Tax Payers file also lacked information on firm employee size.

Since firm size was missing from all lists mentioned above, after having discussed with GSS and with the local contractor the following methods were used to predict firm size. - All firms who were in the Firm Registry but not in the VAT dataset were considered to be micro firms and therefore not use in the current survey. - Firms who were in the Firm Registry and in the VAT dataset were considered to be small firms. - Firms in the Large Tax Payers dataset were considered medium or large firms. The original design was divided into two size groups: small firms and medium and large firms.

During fieldwork the GSS lists proved to be very inaccurate and not sufficient to reach the target sample design, As such they were complemented with additional lists of firms from the Ghana Chamber of Commerce and Industry and Business Associations. The list from the Ghana Chamber of Commerce lacked information on firm employee size or firm turnover. Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 1.3% (26 out of 1,990 establishments).

Finally, a block enumeration was also undertaken in order to build an additional list. The block enumeration allowed to physically creating a list of establishments from which to sample from. A total of 41 blocks were enumerated in the four locations included in the project out of the total 804 blocks identified. The enumeration was conducted without major problems in the time planned. The list of enumerated firms contained 958 records eligible for main Enterprise Survey.

Note: Unlike the standard ES, the universe for the Ghana ES is characterized by the presence of 5 size categories. The category medium&large was added as stratum in order to sample from the GSS large payers list, while the category "unknow size" was included in order to sample the firms in the Chamber of Commerce and Industry list.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame and Units As in all probability sample surveys, it is important that each sampling unit in the surveyed population has a known, non-zero probability of selection. To achieve this, there has to be an appropriate list, or sampling frame of the primary sampling units (PSUs).The universe defined for the GLSS 5 is the population living within private households in Ghana. The institutional population (such as schools, hospitals etc), which represents a very small percentage in the 2000 Population and Housing Census (PHC), is excluded from the frame for the GLSS 5.

The Ghana Statistical Service (GSS) maintains a complete list of census EAs, together with their respective population and number of households as well as maps, with well defined boundaries, of the EAs. . This information was used as the sampling frame for the GLSS 5. Specifically, the EAs were defined as the primary sampling units (PSUs), while the households within each EA constituted the secondary sampling units (SSUs).

Stratification In order to take advantage of possible gains in precision and reliability of the survey estimates from stratification, the EAs were first stratified into the ten administrative regions. Within each region, the EAs were further sub-divided according to their rural and urban areas of location. The EAs were also classified according to ecological zones and inclusion of Accra (GAMA) so that the survey results could be presented according to the three ecological zones, namely 1) Coastal, 2) Forest, and 3) Northern Savannah, and for Accra.

Sample size and allocation The number and allocation of sample EAs for the GLSS 5 depend on the type of estimates to be obtained from the survey and the corresponding precision required. It was decided to select a total sample of around 8000 households nationwide.

To ensure adequate numbers of complete interviews that will allow for reliable estimates at the various domains of interest, the GLSS 5 sample was designed to ensure that at least 400 households were selected from each region.

A two-stage stratified random sampling design was adopted. Initially, a total sample of 550 EAs was considered at the first stage of sampling, followed by a fixed take of 15 households per EA. The distribution of the selected EAs into the ten regions or strata was based on proportionate allocation using the population.

For example, the number of selected EAs allocated to the Western Region was obtained as: 1924577/18912079*550 = 56

Under this sampling scheme, it was observed that the 400 households minimum requirement per region could be achieved in all the regions but not the Upper West Region. The proportionate allocation formula assigned only 17 EAs out of the 550 EAs nationwide and selecting 15 households per EA would have yielded only 255 households for the region. In order to surmount this problem, two options were considered: retaining the 17 EAs in the Upper West Region and increasing the number of selected households per EA from 15 to about 25, or increasing the number of selected EAs in the region from 17 to 27 and retaining the second stage sample of 15 households per EA.

The second option was adopted in view of the fact that it was more likely to provide smaller sampling errors for the separate domains of analysis. Based on this, the number of EAs in Upper East and the Upper West were adjusted from 27 and 17 to 40 and 34 respectively, bringing the total number of EAs to 580 and the number of households to 8,700.

A complete household listing exercise was carried out between May and June 2005 in all the selected EAs to provide the sampling frame for the second stage selection of households. At the second stage of sampling, a fixed number of 15 households per EA was selected in all the regions. In addition, five households per EA were selected as replacement samples.The overall sample size therefore came to 8,700 households nationwide.

Mode of data collection

Face-to-face [f2f]

Abstract

The principal objective of the 2007 Ghana Maternal Health Survey (GMHS) is intended to serve as a source of data on maternal health and maternal death for policymakers and the research community involved in the Reducing Maternal Morbidity and Mortality (R3M) program. Specifically, the data collected in the GMHS is intended to help the Government of Ghana and the consortium of organizations participating in the R3M program to launch a series of collaborative efforts to significantly expand women's access to modern family planning services and comprehensive abortion care (CAC), reduce unwanted fertility, and reduce severe complications and deaths resulting from unsafe abortion. The GMHS collected data from a nationally representative sample of households and women of reproductive age (15-49). The data were collected in two phases. The primary objectives of the 2007 GMHS were: • To collect data at the national level that will allow an assessment of the level of maternal mortality in Ghana for the country as a whole, for the R3M program regions (Greater Accra, Ashanti and Eastern Regions), and for the non-program regions; • To identify specific causes of maternal and non-maternal deaths, and specifically to be able to identify deaths due to abortion-related causes, among adult women; •To collect data on women’s perceptions and experience with antenatal, maternity, and emergency obstetrical care, especially with regard to care received before, during, and after the termination or abortion of a pregnancy; • To measure indicators of the utilization of maternal health services and especially post-abortion care services in Ghana; and • To provide baseline data for the R3M program and for follow-on studies and surveys that will be used to observe possible reductions in maternal mortality as well as reductions in abortion-related mortality.It also contributes to the ever-growing international database on maternal health-related information.

The pregnancy-related mortality ratio (PRMR) for the 7-year period preceding the survey, calculated from the sibling history data, is 451 deaths per 100,000 live births and for the 5-year period preceding the survey is 378 deaths per 100,000 live births.Induced abortion accounts for more than one in ten maternal deaths and the obstetric risk from induced abortion is highest among young women age 15-24. Although almost all women seek antenatal care from a health professional, only one in two women deliver in a health facility, and three in four women seek postnatal care. Despite the emphasis on continuity of care, less than one in two women receive all three maternity care components (antenatal care, delivery care, and postnatal care) from a skilled provider. Clearly, Ghana has a long way to go towards achieving the MDG-5 target.

Geographic coverage

National

Analysis unit

Individual

Universe

1. All women age 12-49 years in households and residents in Ghana

Kind of data

Sample survey data [ssd]

Sampling procedure

To achieve the above-mentioned objectives and to obtain an accurate measure of the causes of maternal mortality at the national level, and for the Reducing Maternal Morbidity and Mortality( R3M) regions (Greater Accra, Ashanti and Eastern regions) and other regions (Western, Central, Volta, Brong Ahafo, Northern, Upper East and Upper West), 1600 primary sampling units were selected (half from the R3M regions and half from the other regions) within the 10 administrative regions of the country, across urban and rural areas. The primary sampling units consisted of wards or subwards drawn from the 2000 Population Census. This sample size was estimated from information in the 2003 Ghana DHS survey; it was expected that each primary sampling unit would yield, on average, 150 households. GSS and GHS enumerators carried out a complete mapping and listing of the 1600 selected clusters. This first phase of data collection yielded a total of 227,715 households.

A short household questionnaire was administered to identify deaths that occurred in the five years preceding the survey to women age 12-49 in each household listed in the selected cluster. In the second phase of data collection a verbal autopsy questionnaire was administered in all households identified in the first phase as having experienced the death of a woman age 12-49. This yielded a total of 4,203 completed verbal autopsy questionnaires.

In the second phase of fieldwork, 400 clusters were randomly selected from the 1600 clusters identified in the first phase. Households with women age 15-49 were selected from these 400 clusters (half from the R3M regions and half from the other regions) and were stratified by region and urban-rural residence to yield 10,858 completed household interviews and 10,370 individual women's interviews. These households were selected randomly and independently from the households identified in the first phase as having experienced a female death.

Institutional populations (those in hospitals, army barracks, etc.) and households residing in refugee camps were excluded from the GMHS sample.

Sampling deviation

No deviation of the original sample design was made

Mode of data collection

Face-to-face [f2f]

Research instrument

The GMHS used four questionnaires: (1) a Phase I short household questionnaire administered at the time of listing; (2) a Phase II verbal autopsy questionnaire administered in households identified at listing as having experienced the death of a female household member age 12-49; (3) a Phase II long-form household questionnaire administered in independently selected households chosen for the individual woman’s interview, and (4) a Phase II questionnaire for individual women age 15-49 in the same phase two selected households. The primary purpose of the short household questionnaire administered at the time of listing during Phase I was to identify deaths to women age 12-49, for administering the verbal autopsy questionnaire on the causes of female deaths, particularly maternal deaths and abortion-related deaths. Unique identifiers for households in phase one and households in phase two were not maintained; therefore households cannot be matched across both phases of the survey. During the first phase of the survey, all households in each selected cluster were listed and administered the short household questionnaire. This questionnaire was administered to identify households that experienced the death of a female [regular] household member in the five years preceding the survey. The verbal autopsy questionnaire (VAQ) was administered during the second phase of fieldwork in those households in which thefemale who died was age 12-49. The VAQ was designed to collect as much information as possible on the causes of all female deaths, to inform the subsequent categorization of maternal deaths, and facilitate specific identification of abortion-related deaths. During the second phase of fieldwork, a longer household questionnaire was administered in the independent subsample of households, to identify eligible women age 15- 49 for the individual woman’s questionnaire and to obtain some background information on the socioeconomic status of these women. The individual questionnaire included the maternal mortality module, which allows for the calculation of direct estimates of pregnancy-related mortality rates and ratios based on the sibling history. The individual questionnaire also gathered information on abortions and miscarriages, the utilization of maternal health services and post-abortion care, women’s knowledge of the legality of abortion in Ghana, the services they have utilized for abortion and if not, the reasons they have not been able to access professional health care for abortions, the places that offer abortion-related care, the persons offering such services, and other related questions. During the design of these questionnaires, input was sought from a variety of organizations that are expected to use the resulting data. After preparation of the questionnaires in English, they were translated into three languages: Akan, Ga, and Ewe. Back translations into English were carried out by people other than the initial translators to verify the accuracy of the translations in the three languages to be used. All problems arising during the translations were resolved before the pretest. The translated questionnaires were pretested to detect any problems in the translations or the flow of the questionnaire, as well as to gauge the length of time required for interviews. GSS and GHS engaged 20 interviewers for approximately two weeks for the pretest (with proficiency in each of the local languages used in the survey). All the pretest interviewers were trained for two weeks. The pretest interviewing took about one week to complete, during which approximately 30 women were interviewed in each of the local languages. The pretest results were used to modify the survey instruments as necessary. All changes in the questionnaire after the pretest were agreed to by GSS, GHS, and Macro. GSS and GHS were responsible for producing a sufficient number of the various questionnaires for the main fieldwork. During the pretest and main survey training, experts in the areas of health and family planning were identified by GSS and GHS to provide guidance in the presentation of topics in their fields, as they relate to the GMHS questionnaires. Other technical documents that were finalized include: • Household listing manual, listing forms and cartographic materials; • Interviewer’s manual; • Supervisor’s manual; • Interviewer and Supervisor’s