This dataset is the proportion of people in the 2018 Census dataset and data sources used to count them by territorial authority / local board (TALB) geography. Coverage compares the proportion of people counted in the census with the number of people that should have been counted on census night. It is usually expressed as a percentage. We are using interim coverage at this time, with the official post-enumeration survey (PES) coverage rates for the 2018 Census being published by March 2020. The dataset shows that whilst there is variation across territorial authority / local board areas in the proportions of people we counted (from 96.3 to >100%), the interim coverage rates for local areas are generally very high. Understanding how we counted people will help you to use the census dataset because it provides more information about the data sources used and the composition of the data in terms of the proportion of: census individual forms received. partial census form responses (via the paper dwelling form or online household summary form but did not receive an individual form for the person). admin enumerations (the use of administrative data to add people to the usually resident census population when a census response has not been received). The higher the proportion of census forms received, the more robust the characteristic data, for example income, occupation, will be within the dataset for variables. This is especially the case where characteristic information cannot be provided from alternative sources such as historic census data, administrative data or imputation. A csv version of this table is also available (attachment below).

Abstract (en): To reduce respondent burden for the 2013 collection, the Census of Jails was combined with the Deaths in Custody Reporting Program (DCRP). The census provides the sampling frame for the nationwide Survey of Inmates in Local Jails (SILJ) and the Annual Survey of Jails (ASJ). Previous jail enumerations were conducted in 1970 (ICPSR 7641), 1972 (ICPSR 7638), 1978 (ICPSR 7737), 1983 (ICPSR 8203), 1988 (ICPSR 9256), 1993 (ICPSR 6648), 1999 (ICPSR 3318), 2005 (ICPSR 20367), and 2006 (ICPSR 26602). The RTI International collected the data for the Bureau of Justice Statistics in 2013. The United States Census Bureau was the collection agent from 1970-2006. The 2013 Census of Jails gathered data from all jail detention facilities holding inmates beyond arraignment, a period normally exceeding 72 hours. Jail facilities were operated by cities and counties, by private entities under contract to correctional authorities, and by the Federal Bureau of Prisons (BOP). Excluded from the census were physically separate temporary holding facilities such as drunk tanks and police lockups that do not hold persons after being formally charged in court. Also excluded were state-operated facilities in Connecticut, Delaware, Hawaii, Rhode Island, Vermont, and Alaska, which have combined jail-prison systems. Fifteen independently operated jails in Alaska were included in the Census. The 2013 census collected facility-level information on the number of confined and nonconfined inmates, number of inmates participating in weekend programs, number of confined non-U.S. citizens, number of confined inmates by sex and adult or juvenile status, number of juveniles held as adults, conviction and sentencing status, offense type, number of inmates held by race or Hispanic origin, number of inmates held for other jurisdictions or authorities, average daily population, rated capacity, number of admissions and releases, program participation for nonconfined inmates, operating expenditures, and staff by occupational category. 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: Created variable labels and/or value labels.; Standardized missing values.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Datasets:DS1: Census of Jails, 2013 All locally, regionally, and federally administered jails in the United States. The respondent universe was derived from a facility list maintained by the Census Bureau for BJS, from correctional association directories, and from other secondary sources. Census forms were sent to each jail jurisdiction. In addition to a paper form, BJS offered respondents an electronic version via the internet, allowing them to complete and submit their completed questionnaires on-line. 2018-04-25 The dataset and the codebook have been updated2016-03-25 Two records needed to be updated. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. mail questionnaire web-based survey

Abstract

The primary mission of the 2006 Population and Housing Census (PHC) of Nigeria was to provide data for policy-making, evidence-based planning and good governance. The Government at all tiers, researchers, the academia, civil society organizations and the international agencies will find the sets of socio-demographic data useful in formulating developmental policies and planning. The 2006 data will certainly provide benchmarks for monitoring the Millennium Development Goals (MDGs). Enumeration in the 2006 PHC was conducted between March 21st and 27th 2006. It was designed to collect information on the quality of the population and housing, under the following broad categories: demographic and social, education, disability, household composition, economic activity, migration, housing and amenities, mortality and fertility. The results of the exercise are being released as per the Commission's Tabulation Plan which began with the release of the total enumerated persons by administrative areas in the country in the Official Gazette of the Federal Republic of Nigeria No.2, Vol 96 of February 2,2009 and followed with the release of Priority Tables that provide some detailed characteristics of the population of Nigeria by State and LGA.

Geographic coverage

National

Analysis unit

Individuals Households

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Census 2006 Processing: The Technology and Methodology:-

Unlike the data capture method used for the country’s previous censuses, where information from the census forms are typed into the computer system, data capture for census 2006 was carried out by OMR/OCR/ICR systems where questionnaires are scanned through high speed optical scanners. The choice of the scanning system was because it is faster and more accurate than the data keying method.

OMR/OCR/ICR Technology

Definition of terms

• OMR (Optical Mark Recognition) - This means the ability of the scanning machine to detect pencil marks made on the questionnaires by the Enumerators in accordance with the responses given by the respondents.
• OCR (Optical Character Recognition) - This means the ability of the scanning machine to recognize machine printed characters on the questionnaires.
• ICR (Intelligent Character Recognition) - This means the ability of the scanner to recognize characters hand written by the Enumerators in accordance with the responses given by the respondents.

Processing Procedures of Census 2006 at the DPCs:- Data processing took place in the Commission’s seven (7) Data Processing Centres located in different geographical zones in the country. There was absolute uniformity in the processing procedures in the seven DPCs.

(a) Questionnaire Retrieval/Archiving Questionnaires from the fields were taken directly from the Local Government Areas to designated DPCs. The forms on arrival at the DPCs were counted, archived and labeled. Retrieval of the questionnaires at the DPCs were carried out based on the EA frame received from the Cartography Department. Necessary Transmittal Forms are completed on receipt of the Forms at the DPCs. The Transmittal Forms are also used to keep track of questionnaires movement within the DPC.

(b) Forms Preparation The scanning machine has been designed to handle A4 size paper. And the Census form being twice that size has to be split into two through the dotted lines at the middle of the form. This forms preparation procedure is to get the questionnaires, for each Enumeration Areas (EAs), ready for scanning. There is a Batch Header to identify each batch.

(c) Scanning Each Batch on getting to the Scanning Room was placed on joggers (a vibrating machine)to properly align the forms, and get rid of dust or particles that might be on the forms.

The forms are thereafter fed into the scanner. There were security codes in form of bar codes on each questionnaire to identify its genuineness. There was electronic editing and coding for badly coded or poorly shaded questionnaires by the Data Editors. Torn, stained or mutilated forms are rejected by the scanner. These categories of forms were later manually keyed into the system.

Re-archiving of Scanned Forms:- Scanned forms were placed in their appropriate marked envelopes in batches, and thereafter returned to the Archiving Section for re-archiving.

Data Output from the Scanning Machine:- The OMR/OCR Software interprets the output from the scanner and translates it into an XML file from where it is further translated into the desired ASCII output that is compatible for use by the CSPro Package for further processing and tabulation.

Data back-up and transfer:- After being sure that the data are edited for each EA batch in an LGA, data then was exported to the SAN (Storage Area Network) of the Server. Two copies of images of the questionnaires for each EA copied to the LTO tapes as backup and then transferred to the Headquarters. The ASCII data files for each LGA are zipped and encrypted, and thereafter transfer to the Data Validation Unit (DVU) at the Headquarters in Abuja.

Data appraisal

Data collation and validation:- The Data Validation Unit at the Headquarters was responsible for collating these data into EAs, LGAs, States and National levels. The data are edited/validated for consistency errors and invalid entries. The Census and Survey Processing (CSPro) software is used for this process. The edited, and error free data are thereafter processed into desired tables.

Activities of the Data Validation unit (DVU):-

Decryption of each LGA Data File Concatenation/merging of Data Files Check each EA batch file for EA completeness within an LGA and State Check for File/Data Structure Check for Range and Invalid Data items Check for Blank and empty questionnaire Check for inter and intra record consistency Check for Skip Patterns Perform Data Validation and Imputation Generate Statistics Report of each function/activity Generate Statistical Tables on LGA, State and National levels.

See story map for coverage and composition rates. Download lookup file from Stats NZ map hub or Stats NZ geographic data service. ​ Interim coverage rates Coverage rates use dual system estimation (DSE) benchmarks as the denominator to calculate interim coverage rates. Dataset contains interim coverage rates for the usually resident population and for people of Māori descent, and for Māori, Pacific, and Asian ethnic groups. Composition rates Dataset contains composition rates (data sources used to count the census usually resident population) for the usually resident population and for each of the six ethnic groups (European; Māori; Pacific; Asian; Middle Eastern, Latin American, and African (MELAA); and Other). Data sources used to count the census usually resident population: Proportion individual response – census individual forms received. Proportion partial response – partial census form responses (from the paper dwelling form or online household set-up form but where an individual form for the person was not received). Proportion admin enumeration – the use of admin data to add people to the usually resident census population when a census response was not received. ​ Footnotes Geographical boundaries Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023.

Abstract

The 2009 Agricultural Census was undertaken by the Samoa Bureau of Statistics in collaboration with the Ministry of Agriculture and Fisheries. The Census collected a large volume of information pertaining to the agricultural activities of households. Enumeration was carried out for 5 weeks in November/December 2009 by enumerators selected from the villages through interview and a basic test. The test included basic mathematical skills, knowledge of agricultural practices and map reading. This was to ensure that the enumerators are of high quality. The officers of the Samoa Bureau of Statistics and the Ministry of Agriculture and Fisheries were allocated to specified areas as supervisors.

Geographic coverage

National

Analysis unit

Households (Agricultural and non-Agricultural) Agricultural Holdings

Kind of data

Census/enumeration data [cen]

Sampling procedure

For any census to be successfully carried out, good household lists and enumeration area maps are pre-requisites. A list of households in respect of each enumeration block in the country was prepared in 2005 for the 2006 Population Census. The updated household list from the 2006 Population Census was used as a frame for the Agricultural Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The methodology for carrying out the census of Agriculture in Samoa was a combination of complete count and sample survey. Thus the census was basically two part operation. The first part involved all households who were required to complete the Household Form. The households identified as agriculturally active from the Household Forms (Subsistence, Subsistence and Cash and Commercial) were required to complete the Holding Form for every holding operated.

The second part of the questionnaire was designed to cover 25 percent of all agricultural holdings as identified in the first part, with selection made on systematic sample basis (every fourth holding selected). Thus while the Household Form was canvassed in respect of all households, the Holding Form was to be completed by agriculturally active Households only and the Parcel Form was completed in respect of 25 percent of the agricultural holdings.

Printing of Questionnaires and Instruction Manuals In all there were three questionnaires and two instruction manuals one in Samoan and one in English. The three questionnaires were printed on different coloured paper for ease of identification. All census documents were printed and distributed well in advance of the start of the field work.

Cleaning operations

The Secretariat of Pacific community (SPC) provided technical assistance for data processing. The TA was delivered in two separate missions, first to implement data entry, and the second mission was to perform data editing and generate final tabulation for final report. Prior to the start of data entry, Siaumau Misela of Samoa Bureau of Statistics was invited to SPC in December 2009 for a two weeks attachment. Misela worked closely with the SPC data processing specialist in developing the data entry system using CSPro (Census and Survey Processing System). The first mission of the data processing specialist in January 2010 was to finalize and implement data entry. The second mission in October 2010 concentrated mainly on data editing, data recode and generating final tables. The data processing (manual and computer) was done in the Data Processing Section of the Samoa Bureau of Statistics. To facilitate the manual and machine processing of the forms, questionnaires from the same enumeration area were bound together in a batch / folio and assigned a batch id. This id consists of the District, Village and the enumeration area codes. These forms were subjected to manual data scrutiny and corrections. The data entry was implemented using ENTRY of CSPro, and BATCH EDIT for the validation of encoded data items. Data entry was run through a network, which link all data entry work station to a server. A team of 6 staff (1 permanent and 5 temporary) were assigned to do the data processing.

Data appraisal

Fifty percent key verification was done on all the batches, and questionnaires with key verification error rate higher than the tolerance limit was subjected to 100 percent key verification. Additional checks were added in the validation program. Detected errors and inconsistencies were corrected in the batch files.

Abstract

There is a long history to the agricultural census in the Netherlands. From 1934 onwards a census has been carried out (almost) every year. In recent years it is no longer purely a statistical project, but serves several purposes: on the one hand production of statistics by Statistics Netherlands and creating a frame for sampling, on the other hand providing data on individual holdings for administrative purposes by the Ministry of Economic Affairs, Agriculture and Innovation (the Ministry). Since the Ministry and Statistics Netherlands have a common interest in the census, it is held as a joint effort. In 1990, it was the last time special meeting days were organised to assess the data from the farmers. On these meeting days, farmers and enumerators jointly filled in the questionnaire manually. In the period 1991 – 1995, these sessions still took place, but the manual procedure was gradually replaced by filling in the information in a computer file. In 1996, the farmer could make a choice between coming to a special meeting place or filling in the survey form himself and returning it by postal mail. From 1997 on, a complete census was organised by postal mail every year. The year 2003 was a pilot year in which respondents had the opportunity to supply the census information through an internet application. In recent years the information is predominantly supplied via the internet. Since the statistical year 2002 the questionnaire of the agricultural census is combined with the application for animal, crop and arable land subsidies (in 2006 also for the single payment scheme). In 2007 data collection for the enforcement of the manure law is also combined in this questionnaire. This is done for efficiency reasons, both for farmers, and for administration and processing of data.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as a single unit, both technically and economically, which has a single management and which undertakes agricultural activities listed in Annex Ito the European Parliament and Council Regulation (EC) No. 1166/2008 within the economic territory of the EU, either as its primary or secondary activity.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Frame Statistics Netherlands has a business register of all industrial and non-industrial commercial establishments, but the agricultural holdings are not yet fully covered in this register. The agricultural census therefore relies on the administrative farm register (AFR) of the Ministry held by NSIR, an executive service of the Ministry. By law farmers have to register with NSIR. The AFR contains names, addresses and a few other characteristics of holders or holdings and a unique registration number. With the census information of several years Statistics Netherlands has built up a statistical farm register (SFR). Relevant characteristics from the AFR (a.o. identification number, addresses, legal status) are also stored in the SFR. Changes in addresses are entered into the AFR throughout the year, changes in the SFR of course only once a year. The SFR provides a magnificent basis for stratification and efficient sampling of subsequent agricultural statistics. An annual census may seem expensive (even when only half of the cost is looked upon as expenses for statistics). But the excellent quality of the sample frame allows for relative small samples in related agricultural statistics and thus reduction of costs.

Mode of data collection

Computer Assisted Web Interview (CAWI)

Research instrument

One questionnaire was used, integrating both the 2010 AC and the SAPM, and presented to respondents as a single statistical inquiry. The questionnaire covered all 16 core items recommended in the WCA 2010.

Questionnaire:

1 Work and education 2 Number of animals and housing 3 Horticulture under glass 4 Mushrooms, bulb growing, chicory growing 5 Crops on open land and land use 6 Agricultural land area 7 Subsidies 8 Farm data 9 Livestock manure 10 Excavation notification (WION) 11 Signature

Cleaning operations

a. Data collection and data entry About 85% of the questionnaires was filled in and returned using the web application, which already contained a lotof c hecks and validations. Paper forms were digitized by a data-entry firm and processed by NSIR in the same way as the online questionnaires. There were several quality controls to ensure correct digitization.

b. Data processing, estimation and analysis Data processing, estimation and analysis were performed in two successive stages:

1. Pre-processing at NSIR After data collection and data entry the input data go through an extensive error control phase. In this phase checks are made on missing values, valid values, unlikely values, range checks, checks of correlation in the data, checks of totals and so on. When necessary additional information is collected from the farmers by phone. Data that is checked and accepted by NSIR is forwarded to Statistics Netherlands.

2. Processing at Statistics Netherlands Processing at Statistics Netherlands involves additional error control, enrichment with additional information, such as total SO and typology, imputation for non-response and analysis. Analyses are made at several levels of aggregation and comprise comparison with previous results and agricultural data from other sources.

Data appraisal

Checking the information in the questionnaires took place using a special control programme. Data were checked for hard and soft errors. Hard errors are non-valid values. Soft errors are unlikely values. If necessary, the checking personnel contacted the respondent to correct for errors. Approximately 85 percent of the questionnaires were completed online. The online questionnaire application contained extensive interactive controls and edits.

Dissemination: Dissemination is done via the Statline database, which is available on the Internet (www.cbs.nl ). In this database, Internet users may select their own indicators and information topics. Short publications on specific subjects are presented in the form of newspaper or Internet articles. Safe access to census microdata is also provided.

Abstract

The agricultural census and the survey on agricultural production methods were conducted jointly, i.e. within the same organisational structure, at the same time, and using a single electronic questionnaire and the same methods of data collection and processing. The agricultural census covered about 1.8 million of agricultural holdings. At all farms participating in the census, respondents were asked about the "other gainful activities carried out by the labour force" (OGA). The frame for the full survey was prepared on the basis of the list of holdings prepared for the census. When creating the list, an object-oriented approach was adopted for the first time, which meant that at the first stage the holdings (objects) were identified, their coordinates defined (they were located spatially) and their holders were identified on the basis of data from administrative sources. For domestic purposes, the farms with the smallest area, as well as those of little economic importance (meeting very low national thresholds) were included in the sample survey carried out jointly with the census. The survey on agricultural production methods was conducted on a sample of approximately 200 thousand farms in respect of the precision requirements set out in Regulation (EC) 1166/2008. The frame prepared for the agricultural census was used as the sampling frame.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as "an agricultural area, including forest land, buildings or their parts, equipment and stock if they constitute or may constitute an organized economic unit as well as rights related to running the farm". Two types of holding were distinguished (i) the natural persons' holdings (to which thresholds were applied) and (ii) legal persons holdings (no threshold applied).

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Frame The frame for the agricultural census and the survey on agricultural production methods was based on the list of agricultural holdings. In the process of the list of farms creation for the needs of AC and SAPM 2010 the objective approach was used for the first time, which meant that on the first stage of work agricultural holdings were identified, its coordinates were defined (farms were located in space), and its holder was determined according to administrative data as described below. The list creation started from identification of all land parcels used for agricultural purposes. The land parcels found in the set of the Agency for Restructuring and Modernisation of Agriculture (including the Records of holdings and Records of producers) were combined into holding and had their holders defined. For the rest of land parcels, the holders were defined from the Records of Land and Buildings, afterwards the data concerning users were updated by the set of Real Property Tax Record.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

A single electronic questionnaire was used for data collection, combining information related to both the AC 2010 and the SAPM. The census covered all 16 core items recommended in the WCA 2010.

Questionnaire:

Section 0. Identifying characters Section 1. Land use Section 2. Economic activity Section 3. Income structure Section 4. Sown and other area Section 5. Livestock Section 6. tractor, machines and equipment Section 7. Use of fertilizers Section 8. Labour force Section 9. Agricultural production methods

Cleaning operations

a. DATA PROCESSING AND ARCHIVING The data captured through the CAPI, CATI and CAWI channels were gathered in the Operational Microdata Base (OMB) built for the AC 2010 and processed there (including control and correction of data, as well as completing the file obtained in the AC with the data obtained from administrative sources, imputed units and estimation for the SAPM). The data, depersonalized and validated in the OMB, were exported to an Analytical Microdata Base (AMB) to conduct analyses, prepare the data set for transmission to Eurostat and develop multidimensional tables for internal and external users.

b. CENSUS DATA QUALITY Except for a few isolated cases, the CAPI and CATI method resulted in fully completed questionnaires. The computer applications used enabled controls for completeness and correctness of the data already at the collection stage, also facilitating the use of necessary definitions and clarifications during the questionnaire completion process. A set of detailed questionnaire completion guidelines was developed and delivered during training sessions.

Data appraisal

The preliminary results of the agricultural census were published in February 2011 (basic data at the national level), and then in July 2011 in the publication entitled "Report on the Results of the 2010 Agricultural Census" (in a broader thematic scope, at NUTS3 2 level). The final results of the AC 2010 were disseminated by a sequence of publications, covering the main thematic areas of the census. The reference publications were released in paper form, and are available online (www.stat.gov.pl http://www.stat.gov.pl), and on CD-ROMs.

Modeled on the Community Survey of the Project on Human Development in Chicago Neighborhoods, the proposed project collected survey data from random samples of individuals from a random sample of “neighborhood clusters” in El Paso County, Texas. Neighborhood clusters consist of geographically contiguous and socially similar census tracts and for El Paso will be determined by a combination of the local knowledge possessed by the project’s researchers, preliminary analyses of the most recent census data regarding the distributions of immigrant status, language use, year of entry, and aspects of economic disadvantage as well as obvious boundaries (such as Interstates, major roads, mountains, and military installations). The project used a sampling frame of neighborhood clusters in El Paso County stratified by measures of immigrant concentration (e.g., generational status, length of time since immigration) and socio-economic status. The project then employed Cole Lists, a company that provides consumer information for direct marketers, to obtain a list of all residential addresses in El Paso County by census tract. From each sampled neighborhood cluster, 30 residences were selected using a systematic random sampling procedure (a random start determined from a table of random numbers and then selecting every kth address. Each selected residence was mailed a notification letter, printed in English and in Spanish, regarding participation in the project and which specified that a trained interviewer will personally visit to determine which adult resident(s), if any, are willing to participate. For residences that agreed to participate, the adult resident who had the most recent birthday was selected for actual participation. These respondents received an incentive of $20. In face-to-face interviews, trained interviewers recorded each respondent’s answers on a paper form and later manually entered this information into a computer file using spreadsheet software.

Abstract

Tanzania Mainland through the National Bureau of Statistics (NBS) has been conducting the household budget surveys (HBSs) since 1969 to collect data on consumption, expenditure and the poverty situation in the country. The first round of scientific HBSs that represented urban and rural areas was conducted in 1991. Since then NBS has successfully completed five rounds of scientific HBS including the 2017- 18 HBS. The HBS data series is the major sources of information for estimation of poverty and its associated characteristics. It provides empirical evidence for users to understand the income (using the consumption expenditure as proxy to income) dimension of poverty.

Objectives of the Survey: The main objective of the 2017-18 HBS was to obtain current information on poverty estimation and its associated characteristics and to assess the progress made in improving the living standards of the people. The result will be used for monitoring the implementation of national, regional and global commitments such as Tanzania Development Vision 2025, national Second Five Year Development Plan (FYDP-II 2016/17 2020/21), East Africa Community Vision 2050 (EAC 2050), Africa Development Agenda 2063 (ADA 2063) and Global Agenda 2030 on Sustainable Development Goals (2030 SDGs). Specifically, the 2017-18 HBS aimed at: - Providing series of data for assessing poverty and changes in the households' living standards over time; and for monitoring and evaluation of the impacts of socio-economic policies and programs on the welfare of people; - Providing baseline data for compiling household accounts such as the Private Final Consumption Expenditure (PFCE) component of the demand side of Gross Domestic Product (GDP) as recommended in the System of National Accounts (SNA); and - Rebasing of GDP and Consumer Price Indices (CPI).

Geographic coverage

• National coverage
• Rural and urban areas
• Regions: Dodoma, Arusha, Kilimanjaro, Tanga, Morogoro, Pwani, Dar es Salaam, Lindi, Mtwara, Ruvuma, Iringa, Mbeya, Singida, Tabora, Rukwa, Kigoma, Shinyanga, Kagera, Mwanza, Mara, Manyara, Njombe, Katavi, Simiyu, Geita, and Songwe.

Analysis unit

• Individuals
• Households
• Communities

Universe

The survey covered all members residing in private households in Tanzania Mainland.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2017-18 HBS covered the population residing in private households in Tanzania Mainland. A representative probability sample of 9,552 households was selected. This sample was designed to allow separate estimates for each of the 26 regions of the Tanzania Mainland, also urban and rural areas separately at the national level.

The 2017-18 HBS adopted a two-stage cluster sample design. The first stage involved selection of enumeration areas (primary sampling units - PSUs) from the 2012 Population and Housing Census (2012 PHC) Frame. A total of 796 PSUs (69 from Dar es Salaam, 167 from Other Urban Areas and 560 from Rural Areas) was selected. The NBS carried out listing exercise in which households residing in selected PSUs were freshly listed to update the 2012 PHC list before selecting households.

The second stage of sampling involved systematic sampling of households from the updated PSUs list. A sample of 12 households was selected from each selected PSU. All household members regardless of their age, who were usual members of the selected households and all visitors who were present in the household on the night before the survey interview, were eligible for the survey.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2017-18 HBS was implemented using six electronic questionnaires (Forms I - V and VII) and a paper questionnaire (Form VI). The information collected was the following: - Form I: Demographics; parents' survivorship; birth delivery and breast feeding; citizenship and migration; education; literacy; health; disability; insurances, individual asset ownership and identification documents; labour market indicators; non-farm household businesses; and individual non-wage income; - Form II: Dwellings; utility; water and sanitation; transport and communications; tourism; investments; banking; and households’ recall expenditures; children and adult mortality. The form also contained the TASAF and food security modules; - Form III: Crops, livestock and food security; - Form IV: Time use (5+ years Household members); - Form V: Household diary for recording daily household consumption and expenditure over a 14-days period; - Form VI: Individual diary for recording daily consumption and expenditure for each household member age five years or more; and - Form VII: Access to community services (selected communities).

More details on the questionnaire are provided as external resources

Response rate

Out of 9,552 selected households, 9,465 households participated in the survey yielding a response rate of 99 percent.

Poverty and empowerment impacts of the Bihar Rural Livelihoods Project: Evidence from a Mixed-Methods Cluster-Randomized Trial Jeevika is a World Bank assisted project focussed (now under the umbrella of the NRLM) on building networks of women's self-help credit and savings groups,and then using them as a base of other "vertical" interventions. This houshold and village survey data was collected over two rounds to conduct an impact evaluation of Phase 2 of the project with random assignment of the project over a two year period. Collaboration: World Bank Social Observatory team with Government of Bihar. Evaluation design, methods and implementation In order to evaluate the impacts of Jeevika, 180 panchayats were randomly selected from within 16 blocks in seven districts where scale-up of the project was planned but had not yet occurred. Some of these blocks were in districts relatively far from Patna, which had not yet been entered by the project (Madhepura, Saharsa, Supaul), while others were within the larger districts within which Jeevika was already operating (Gaya, Nalanda, Madhubani, Muzaffarpur). The project had already entered these districts in Phase 1, but had not yet expanded to all blocks due to (project) capacity constraints. Within each of the study villages, hamlets (tolas) in which the majority of the population belonged to a scheduled caste or scheduled tribe were identified. This was the same procedure as used by Jeevika to identify the target population (of poor women) for mobilization into the project. Tolas were identified through a focus group discussion held in each village, along with the population of target castes (SC/STs) within each. In Bihar, tola boundaries are easily distinguishable. Field teams would enter the tola at a random point, determine the skip pattern based on the population size and target sample size, and select households through a random walk. Survey staff aimed to include 70% SC/ST households, and 30% households from other castes in each village, in order to ensure variation in socio-economic status within the sample. If the households in selected tolas included fewer SC/ST households than this, households from nearby non-SC/ST majority tolas were also included in the sample. Interviews for the quantitative study were conducted using a structured paper survey form. Baseline and follow up surveys included detailed questions on debt, asset holdings, consumption expenditures, livelihood activities, and women’s mobility, role in household decisions, and aspirations. In addition, in each village, a focus group discussion was conducted, through which data were collected on village level attributes such as local sources of credit, interest rates from each source, local wage rates, and the presence of or distance to markets and other institutions and amenities. Respondents were not compensated for their time. If a respondent was unavailable during initial field visit, the supervisor recorded contact details and returned with interviewers at a later date. As long as the survey team was in that district, repeat visits were undertaken, keeping attrition to a minimum. If a household could not be re-surveyed at endline, it was replaced with another household in the same village. Short re-surveys containing a subset of questions from the main survey were conducted by supervisors for 10% of the sample. Staff from the project also conducted occasional visits after the survey was completed in a village to confirm that all modules had been covered by survey staff. Data was entered in duplicate using CSPro and any discrepancies were corrected based on the paper form. Following the baseline survey, panchayats were stratified on the 16 administrative blocks in the sample and the panchayat-level mean of outstanding high cost (monthly interest rate of 4% or higher) debt held by households at baseline. They were then randomly assigned to an early rollout group or a late rollout group using the random number generator within the Stata statistical analysis software package. The baseline survey was administered to 8988 households across 333 villages in 179 panchayats. The target number of households per panchayat was 50, but there was some variation around this in reality. The lowest number of households in a given panchayat was 49 (9 panchayats), and the largest number was 53 households (3 panchayats). To ensure that control panchayats were not entered by the project, Jeevika held a quarterly ""evaluation panchayat"" meeting, which block project managers of the 16 blocks were required to attend. At these meetings the project M&E team checked whether any village in a control panchayat had been entered, and received an update on progress in treatment panchayats. This procedure was successful in maintaining adherence to randomized treatment assignment throughout the evaluation period. Of the 4,472 households in the sample across 89 panchayats allocated to receive the SHG intervention,...

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.

End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).


How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

The sixth sweep of the Millennium Cohort Study was carried out when the cohort members were 14 years old. As 14 is a key transitional age, the sweep was purposefully ambitious in the breadth and scope of its contents. It included: an interview (CAPI and CASI) with the main parent and their partner (where relevant); a self-completion interview with the cohort members; cognitive assessments for the main parent, the partner and the cohort member; DNA collection of the cohort member and natural parents in the household; physical measurements of the cohort member; placement of a time use diary with the cohort member; placement of an accelerometer with the cohort member.

For the seventh edition (November 2020), three additional cohort member Time Use Diary (TUD) data files have been added. There is a separate data file for each mode of data collection (paper form, mobile application and online form). The harmonised TUD data file is still available which combines all three modes of data collection.