Attitude of the German population and of critics of the census to the census after census day on 31 May 1987. Political attitudes. Topics: political interest; satisfaction with democracy in the Federal Republic; government orientation toward its own interests or public interest; perceived protection of rights to freedom by the political system and the current Federal Government; satisfaction with the job of the Federal Government; attitude to the census; receipt of a written request to fill out the questionnaire; intent to participate in the census before start of counting; personal willingness to participate in the census even given voluntary participation; assumed level of non-participation in the census; attitude to the census in one´s circle of friends and acquaintances; conversations about the census in social surroundings after conclusion of the survey and time of last conversation; knowledge about contents of the census survey; additionally expected questions; questions that one would not gladly answer; response or boycott behavior during the survey; attitude to government statistics; attitude to punishment of census boycotters and knowledge of cases of refusal; assumed willingness of the population to participate as well as honesty of responses given voluntary participation in the census; voluntarily providing selected personal data; preference for census or providing data already available by government offices; assumed benefit or damage from discussions about the census in the media and reasons for this assessment; attitude to earlier calls for boycott and to the time of survey; judgement on the success of the boycott movement; attitude to selected arguments for and against the census; benefit of a census; attitude to the obligation to provide information; census boycott as protest against the government; census participation as democratic duty; self-assessment on a left-right continuum; assumed position of the majority of the population on a left-right continuum; understanding of democracy and comparison of this right with reality in the Federal Republic; party preference; violation of fundamental rights by measures of authorities perceived personally or by persons from social surroundings; attitude to technology; perceived insecurity in contact with authorities and attitude to government offices; concerns regarding misuse of personal census data; trust in observance of data protection; attitude to storage of personal data; importance of data protection; assumed observance of data protection regulations; knowledge of cases of data misuse and source of information about such violations; assumed willingness to participate in a future census; attitude to opinion polls (scale); willingness to participate in a microcensus survey; willingness to provide information from one´s private sphere to friends, neighbors, census bureaus and scientific surveys; attitude to selected government statistics; willingness to respond in order to make statistics possible; fear of data misuse; concerns regarding misuse of personal data by selected institutions and government offices (scale); attitude to selected illegal actions (scale); religiousness (scale); attitude to questions of belief and the meaning of life (scale); belief in supernatural, inexplicable events as well as horoscopes and telepathy. Demography: month of birth; year of birth; sex; religious denomination; school education; employment; college in vicinity of place of residence; students in residential area; possession of a telephone. Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person causing the intervention; attitude to the census of other persons present during interview; presence of further persons in other rooms; reliability and willingness of respondent to cooperate. Additionally encoded were: length of interview; date of interview; identification of interviewer; sex of interviewer; age of interviewer. Einstellung der bundesdeutschen Bevölkerung und von Volkszählungskritikern zur Volkszählung nach dem Stichtag am 31. Mai 1987. Politische Einstellungen. Themen: Politisches Interesse; Zufriedenheit mit der Demokratie in der Bundesrepublik; Interessen- oder Gemeinwohlorientierung der Regierung; empfundener Schutz der Freiheitsrechte durch das politische System und die gegenwärtige Bundesregierung; Zufriedenheit mit der Arbeit der Bundesregierung; Einstellung zur Volkszählung; Erhalt einer schriftlichen Aufforderung zum Ausfüllen des Fragebogens; Teilnahmeabsicht an der Volkszählung vor Beginn der Zählung; eigene Bereitschaft zur Teilnahme an der Volkszählung, auch bei freiwilliger Teilnahme; vermutete Höhe der Nichtbeteiligung an der Volkszählung; Einstellung zur Volkszählung im Freundes- und Bekanntenkreis; Gespräche über die Volkszählung im sozialen Umfeld nach Abschluß der Erhebung und Zeitpunkt des letzten Gesprächs; Kenntnisse über die Inhalte der Volkszählungsbefragung; zusätzlich erwartete Fragen; Fragen, die ungern beantwortet wurden; Antwort- bzw. Boykottverhalten bei der Erhebung; Einstellung zu staatlichen Statistiken; Einstellung zu einer Bestrafung von Volkszählungsboykotteuren und Kenntnis von Verweigerungsfällen; vermutete Teilnahmebereitschaft der Bevölkerung sowie der Antwortehrlichkeit bei Freiwilligkeit der Teilnahme an der Volkszählung; freiwillige Weitergabe ausgewählter persönlicher Daten; Präferenz für Volkszählung oder Weitergabe von bereits vorliegenden Daten durch die Ämter; vermuteter Nutzen oder Schaden der Diskussion über die Volkszählung in den Medien und Gründe für diese Einschätzung; Einstellung zu früheren Boykottaufrufen und zum Befragungszeitpunkt; Beurteilung des Erfolgs der Boykottbewegung; Einstellung zu ausgewählten Argumenten für und gegen die Volkszählung; Nutzen einer Volkszählung; Einstellung zur Auskunftspflicht; Volkszählungsboykott als Protest gegen den Staat; Volkszählungsteilnahme als demokratische Pflicht; Selbsteinschätzung auf einem Links-Rechts-Kontinuum; vermutete Position der Bevölkerungsmehrheit auf einem Links-Rechts-Kontinuum; Demokratieverständnis und Vergleich dieses Anspruchs mit der Wirklichkeit in der Bundesrepublik; Parteipräferenz; persönlich oder von Personen des sozialen Umfelds empfundene Verletzung der Grundrechte durch Behördenmaßnahmen; Einstellung zur Technik; empfundene Unsicherheiten bei Behördenkontakten und Einstellung gegenüber Ämtern; Befürchtungen hinsicht lich einer Zweckentfremdung der persönlichen Volkszählungsdaten; Vertrauen in die Einhaltung des Datenschutzes; Einstellung zur Speicherung personenbezogener Daten; Wichtigkeit des Datenschutzes vermutete Einhaltung der Datenschutzbestimmungen; Kenntnis von Fällen des Datenmißbrauchs und Informationsquelle über solche Verstöße; vermutete Teilnahmebereitschaft an einer zukünftigen Volkszählung; Einstellung zu Meinungsumfragen (Skala); Teilnahmebereitschaft an einer Mikrozensus-Erhebung; Weitergabebereitschaft von Informationen aus der Privatsphäre an Freunde, Nachbarn, statistische Ämter und in wissenschaftlichen Umfragen; Einstellung zu ausgewählten staatlichen Statistiken; Antwortbereitschaft, um Statistiken zu ermöglichen; Angst vor Datenmißbrauch; Befürchtungen hinsichtlich einer Zweckentfremdung der persönlichen Daten durch ausgewählte Institutionen und Ämter (Skala); Einstellung zu ausgewählten illegalen Handlungen (Skala); Religiosität (Skalometer); Einstellung zu Glaubensfragen und zum Sinn des Lebens (Skala); Glaube an übersinnliche, unerklärliche Ereignisse sowie an Horoskope und Telepathie. Demographie: Geburtsmonat; Geburtsjahr; Geschlecht; Konfession; Schulbildung; Berufstätigkeit; Hochschule in Wohnortnähe; Studenten in der Wohngegend; Telefonbesitz. Interviewerrating: Anwesenheit Dritter beim Interview und Person, die die Anwesenheit erwünschte; Eingriffe Dritter in das Interview und Person, die die Intervention herbeiführte; Einstellung der beim Interview zusätzlich anwesenden Person zur Volkszählung; Anwesenheit weiterer Personen in anderen Räumen; Kooperationsbereitschaft und Zuverlässigkeit des Befragten. Zusätzlich verkodet wurde: Interviewdauer; Interviewdatum; Intervieweridentifikation; Interviewergeschlecht; Intervieweralter. Re-interview of the persons interviewed in the second panel wave (ZA Study No. 1589) as well as of persons interviewed in the first panel wave (ZA Study No. 1588), but not contacted in the survey of the second panel wave. Wiederbefragung der in der 2. Panel-Welle befragten Personen (ZA-Studien-Nr. 1589) sowie von Personen, die in der 1. Panel-Well interviewt wurden (ZA-Studien-Nr. 1588), bei der Befragung der 2. Panel-Welle aber nicht angetroffen wurden.

Attitude of the Federal German population and census critics to the census on 31. May 1987.

Summary of three data sets archived and described under ZA Study Nos. 1588 to 1590.

Topics: 1. From the first wave of 1987: political interest; satisfaction with democracy in the Federal Republic; feeling of political effectiveness and degree of representation by politicians and parties; orientation of government policies on special interests or public welfare; attitude to the census; intent of members of household and respondent to participate; willingness to participate after notice of threat of fine; filling out the survey form oneself or by another person in household; conversations about the census in social surroundings and time of last conversation; attitude to the census in circle of friends and acquaintances as well as their willingness to participate; importance of political attitudes in social surroundings and visibility of one´s own views; knowledge about contents of the census survey (scale); assumed difficulty in filling out survey form; preference for filling out the form in the presence of the canvasser or alone; misgivings about canvasser in residence; difficulties in carrying out official matters; frequency of contact and ability to establish contacts; trust in institutions and organizations; self-assessment on a left-right continuum; assumed position of the majority of the population on a left-right continuum; postmaterialism; sympathy scale for political parties; frequency of use of television news broadcasts as well as the local part and political part of a daily newspaper; time of last noticed media reports about the census and content tendency of these programs; assumed attitude of the population to the census; living together with a partner and his attitude to the census; assumed participation of partner in the census; response or boycott conduct in the census survey; attitude to government statistics; attitude to punishment of census boycotters and preferred governmental behavior regarding refusal; personal fears regarding misuse of personal census data; trust in observance of data protection; sympathies regarding social movements as well as personal membership; party preference; perceived fears and their causes; attitude to technology; attitude to computers and scientific innovations; attitude to government dealing with data; assessment of census refusers as system opponents; attitude to storage of personal data; importance of data protection and trust in observance of the data protection regulation; judgement on quality of data protection; earlier participation in a survey and type of survey; attitude to selected infringements and crimes as well as other illegal actions (scale); religiousness; union membership; self-assessment of social class; possession of a telephone; willingness to participate in a re-interview.

The following additional questions were posed to persons with strong or very strong political interest: demographic information on circle of close friends (ego-centered network); agreement with respondent regarding party preference and attitude to the census; willingness of friends to participate in the census; familiarity of friends among each other; personal willingness to participate in selected political forms of protest (scale); personal fears regarding misuse of personal data by selected institutions and public offices.

Demography: month of birth; year of birth; sex; marital status; number of children; ages of children (classified); frequency of church attendance; school education; vocational training; occupation; occupational position; employment; monthly net income of respondent and household altogether; number of persons contributing to household income; size of household; position of respondent in household; characteristics of head of household; number of persons eligible to vote in household; persons in household who do not have German citizenship; self-assessment of social class; union membership of respondent and other members of household; possession of a telephone.

Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person introducing the intervention; attitude to the census of persons additionally present during interview; presence of further persons in other rooms; willingness to cooperate and reliability of respondent.

Also encoded was: length of interview; date of interview; identification of interviewer; sex of interviewer; age of interviewer.

1. From the second wave of 1987: political interest; attitude to the census; conversations about the census in social surroundings and topics discussed; attitude to the census in circle of friends and acquaintances; perceived attitude of the population to the census; time of personal decision making on the census; changes in attitude to the census; personally knowing the canvasser; manner of receipt of questionnaire;...

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Industry titles and their 4-digit codes are based on the 2017 North American Industry Classification System. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..Occupation titles and their 4-digit codes are based on the 2018 Standard Occupational Classification..The Class of Worker status "unpaid family workers" may have earnings. Earnings reflect any earnings from all jobs held during the 12 months prior to the ACS interview. The Class of Worker status reflects the job or business held the week prior to the ACS interview, or the last job held by the respondent..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..Beginning in data year 2019, respondents to the Weeks Worked question provided an integer value for the number of weeks worked. For data years 2008 through 2018, respondents selected a category corresponding to the number of weeks worked..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in ...

Abstract

The 2000 Republic of Palau Census of Population and Housing was the second census collected and processed entirely by the republic itself. This monograph provides analyses of data from the most recent census of Palau for decision makers in the United States and Palau to understand current socioeconomic conditions. The 2005 Census of Population and Housing collected a wide range of information on the characteristics of the population including demographics, educational attainments, employment status, fertility, housing characteristics, housing characteristics and many others.

Geographic coverage

National

Analysis unit

• Household;
• Individual.

Universe

The 1990, 1995 and 2000 censuses were all modified de jure censuses, counting people and recording selected characteristics of each individual according to his or her usual place of residence as of census day. Data were collected for each enumeration district - the households and population in each enumerator assignment - and these enumeration districts were then collected into hamlets in Koror, and the 16 States of Palau.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2000 censuses of Palau employed a modified list-enumerate procedure, also known as door-to-door enumeration. Beginning in mid-April 2000, enumerators began visiting each housing unit and conducted personal interviews, recording the information collected on the single questionnaire that contained all census questions. Follow-up enumerators visited all addresses for which questionnaires were missing to obtain the information required for the census.

Cleaning operations

The completed questionnaires were checked for completeness and consistency of responses, and then brought to OPS for processing. After checking in the questionnaires, OPS staff coded write-in responses (e.g., ethnicity or race, relationship, language). Then data entry clerks keyed all the questionnaire responses. The OPS brought the keyed data to the U.S. Census Bureau headquarters near Washington, DC, where OPS and Bureau staff edited the data using the Consistency and Correction (CONCOR) software package prior to generating tabulations using the Census Tabulation System (CENTS) package. Both packages were developed at the Census Bureau's International Programs Center (IPC) as part of the Integrated Microcomputer Processing System (IMPS).

The goal of census data processing is to produce a set of data that described the population as clearly and accurately as possible. To meet this objective, crew leaders reviewed and edited questionnaires during field data collection to ensure consistency, completeness, and acceptability. Census clerks also reviewed questionnaires for omissions, certain inconsistencies, and population coverage. Census personnel conducted a telephone or personal visit follow-up to obtain missing information. The follow-ups considered potential coverage errors as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Following field operations, census staff assigned remaining incomplete information and corrected inconsistent information on the questionnaires using imputation procedures during the final automated edit of the data. The use of allocations, or computer assignments of acceptable data, occurred most often when an entry for a given item was lacking or when the information reported for a person or housing unit on an item was inconsistent with other information for that same person or housing unit. In all of Palau’s censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in place of blanks or unacceptable entries enhanced the usefulness of the data.

Sampling error estimates

Human and machine-related errors occur in any large-scale statistical operation. Researchers generally refer to these problems as non-sampling errors. These errors include the failure to enumerate every household or every person in a population, failure to obtain all required information from residents, collection of incorrect or inconsistent information, and incorrect recording of information. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires. To reduce various types of non-sampling errors, Census office personnel used several techniques during planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Census staff implemented several coverage improvement programs during the development of census enumeration and processing strategies to minimize under-coverage of the population and housing units. A quality assurance program improved coverage in each census. Telephone and personal visit follow-ups also helped improve coverage. Computer and clerical edits emphasized improving the quality and consistency of the data. Local officials participated in post-census local reviews. Census enumerators conducted additional re-canvassing where appropriate.

Tags

   survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES




   Summary


   BES Research, Applications, and Education


   Description


   Geocoded for Baltimore County. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 



   The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 


   Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey.


   This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because

In Austria a population census takes place every 10 years; this census contains a program of important statistical data on population and employment. They roughly corresponds to the information in the Mikrozensus standard survey but are more detailed (for instance with question on the connection of the place of residence and the workplace, questions on education, confession, etc.) Population and Mikrozensus are closely linked which the name already implies: Mikrozensus means a small-scale population census; this should demonstrate that what the population census reports only every 10 years, the Mikrozensus reports through the method of ongoing sampling. These ongoing sample are also collected in the years of the population census. The Mikrozensus however is far more detailed than the survey program of the population census because the Mikrozensus special surveys offer the possibility of asking questions which are fare beyond the scope of the population census. This complementary function of Mikrozensus and population census becomes especially obvious in the June-survey: certain questions that could not be posed in the population census due to the limited program were answered in the Mikrozensus via sampling. These were the topics: questions on the social stratification of the population questions on fertility and succession of birth questions on the silent Human Resources Probability: Stratified: Proportional Face-to-face interview

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The Class of Worker status "unpaid family workers" may have earnings. Earnings reflect any earnings from all jobs held during the 12 months prior to the ACS interview. The Class of Worker status reflects the job or business held the week prior to the ACS interview, or the last job held by the respondent..In 2019, methodological changes were made to the class of worker question. These changes involved modifications to the question wording, the category wording, and the visual format of the categories on the questionnaire. The format for the class of worker categories are now listed under the headings "Private Sector Employee," "Government Employee," and "Self-Employed or Other." Additionally, the category of Active Duty was added as one of the response categories under the "Government Employee" section for the mail questionnaire. For more detailed information about the 2019 changes, see the 2016 American Community Survey Content Test Report for Class of Worker located at http://www.census.gov/library/working-papers/2017/acs/2017_Martinez_01.html..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Abstract

The survey was one of three components of a World Bank project implemented to provide information on the size and composition of the civil service, improve systems and control mechanisms, institutional capacity, and provide information on policy-formulation and decision-making processes. Other components included a census of Guatemalan civil servants and contractors, and the continuous updating and use of this information to strengthen checks and improve transparency, and a new policy framework aimed at strengthening the institutional capacity of the Guatemalan civil service.

The aim of the survey was to assess the characteristics and quality of human resource management in the public administration, as well as to capture the attitudes, motivations, and experiences of public officials. In particular, the survey focused on the priority areas for reform identified by the Government of Guatemala and the World Bank. The data collected was used to support the World Bank’s diagnostic of key problem areas in the human resource management of the public administration in Guatemala. It was used to inform the design of institution-level interventions, as well as the new public policy framework.

Geographic coverage

The target population were civil servants across 18 institutions in Guatemala at the central, and their respective departmental and municipal branches.

Analysis unit

Public servants (managers and non-managers) across 18 institutions in Guatemala at the central, and their respective departmental and municipal branches.

Kind of data

Aggregate data [agg]

Sampling procedure

The sample frame used comes from the frame used for the Human Resources National Census. It has the list of positions in all the units of the 18 institutions selected for this study. The sample size for the managerial level was calculated with a 95% confidence level and a 5% margin error for each institution. For the non-managers, it was calculated with the same confidence level and margin error. The sample sizes are adjusted so the sample would have an even number for each study domain for the experiment which will assign a different questionnaire to half of the respondents.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire comprises following modules: 1- Pre-interview questions, 2- Demographic and work history information, 3- Management practices, 4- Performance evaluation, 5- perceptions about discrimination, 6- Human resources management practices, 7- Perceptions of the national office of the civil service, 8- Perception of acts of corruption, and 9- Review of surveys.

The questionnaire was prepared in English and Spanish.

Response rate

Response rate was 96%.

Abstract

This study is an experiment designed to compare the performance of three methodologies for sampling households with migrants:

• a stratified sample using the census to sample census tracts randomly, in which each household is then listed and screened to determine whether or not it has a migrant, with the full length questionnaire then being applied in a second phase only to the households of interest;
• a snowball survey in which households are asked to provide referrals to other households with migrant members;
• an intercept point survey (or time-and-space sampling survey), in which individuals are sampled during set time periods at a prespecified set of locations where households in the target group are likely to congregate.

Researchers from the World Bank applied these methods in the context of a survey of Brazilians of Japanese descent (Nikkei), requested by the World Bank. There are approximately 1.2-1.9 million Nikkei among Brazil’s 170 million population.

The survey was designed to provide detail on the characteristics of households with and without migrants, to estimate the proportion of households receiving remittances and with migrants in Japan, and to examine the consequences of migration and remittances on the sending households.

The same questionnaire was used for the stratified random sample and snowball surveys, and a shorter version of the questionnaire was used for the intercept surveys. Researchers can directly compare answers to the same questions across survey methodologies and determine the extent to which the intercept and snowball surveys can give similar results to the more expensive census-based survey, and test for the presence of biases.

Geographic coverage

Sao Paulo and Parana states

Analysis unit

Japanese-Brazilian (Nikkei) households and individuals

The 2000 Brazilian Census was used to classify households as Nikkei or non-Nikkei. The Brazilian Census does not ask ethnicity but instead asks questions on race, country of birth and whether an individual has lived elsewhere in the last 10 years. On the basis of these questions, a household is classified as (potentially) Nikkei if it has any of the following: 1) a member born in Japan; 2) a member who is of yellow race and who has lived in Japan in the last 10 years; 3) a member who is of yellow race, who was not born in a country other than Japan (predominantly Korea, Taiwan or China) and who did not live in a foreign country other than Japan in the last 10 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) Stratified random sample survey

Two states with the largest Nikkei population - Sao Paulo and Parana - were chosen for the study.

The sampling process consisted of three stages. First, a stratified random sample of 75 census tracts was selected based on 2000 Brazilian census. Second, interviewers carried out a door-to-door listing within each census tract to determine which households had a Nikkei member. Third, the survey questionnaire was then administered to households that were identified as Nikkei. A door-to-door listing exercise of the 75 census tracts was then carried out between October 13th, 2006, and October 29th, 2006. The fieldwork began on November 19, 2006, and all dwellings were visited at least once by December 22, 2006. The second wave of surveying took place from January 18th, 2007, to February 2nd, 2007, which was intended to increase the number of households responding.

2) Intercept survey

The intercept survey was designed to carry out interviews at a range of locations that were frequented by the Nikkei population. It was originally designed to be done in Sao Paulo city only, but a second intercept point survey was later carried out in Curitiba, Parana. Intercept survey took place between December 9th, 2006, and December 20th, 2006, whereas the Curitiba intercept survey took place between March 3rd and March 12th, 2007.

Consultations with Nikkei community organizations, local researchers and officers of the bank Sudameris, which provides remittance services to this community, were used to select a broad range of locations. Interviewers were assigned to visit each location during prespecified blocks of time. Two fieldworkers were assigned to each location. One fieldworker carried out the interviews, while the other carried out a count of the number of people with Nikkei appearance who appeared to be 18 years old or older who passed by each location. For the fixed places, this count was made throughout the prespecified time block. For example, between 2.30 p.m. and 3.30 p.m. at the sports club, the interviewer counted 57 adult Nikkeis. Refusal rates were carefully recorded, along with the sex and approximate age of the person refusing.

In all, 516 intercept interviews were collected.

3) Snowball sampling survey

The questionnaire that was used was the same as used for the stratified random sample. The plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (a) a Nikkei household with a member currently in Japan; (b) a Nikkei household with a member who has returned from Japan; (c) a Nikkei household without members in Japan and where individuals had not returned from Japan.

The snowball survey took place from December 5th to 20th, 2006. The second phase of the snowballing survey ran from January 22nd, 2007, to March 23rd, 2007. More associations were contacted to provide additional seed names (69 more names were obtained) and, as with the stratified sample, an adaptation of the intercept survey was used when individuals refused to answer the longer questionnaire. A decision was made to continue the snowball process until a target sample size of 100 had been achieved.

The final sample consists of 60 households who came as seed households from Japanese associations, and 40 households who were chain referrals. The longest chain achieved was three links.

Mode of data collection

Face-to-face [f2f]

Research instrument

1) Stratified sampling and snowball survey questionnaire

This questionnaire has 36 pages with over 1,000 variables, taking over an hour to complete.

If subjects refused to answer the questionnaire, interviewers would leave a much shorter version of the questionnaire to be completed by the household by themselves, and later picked up. This shorter questionnaire was the same as used in the intercept point survey, taking seven minutes on average. The intention with the shorter survey was to provide some data on households that would not answer the full survey because of time constraints, or because respondents were reluctant to have an interviewer in their house.

2) Intercept questionnaire

The questionnaire is four pages in length, consisting of 62 questions and taking a mean time of seven minutes to answer. Respondents had to be 18 years old or older to be interviewed.

Response rate

1) Stratified random sampling 403 out of the 710 Nikkei households were surveyed, an interview rate of 57%. The refusal rate was 25%, whereas the remaining households were either absent on three attempts or were not surveyed because building managers refused permission to enter the apartment buildings. Refusal rates were higher in Sao Paulo than in Parana, reflecting greater concerns about crime and a busier urban environment.

2) Intercept Interviews 516 intercept interviews were collected, along with 325 refusals. The average refusal rate is 39%, with location-specific refusal rates ranging from only 3% at the food festival to almost 66% at one of the two grocery stores.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

Abstract

The 2009 Population and Housing Census was implemented according to Prime Ministerial Decision No. 94/2008/QD-TTg dated 10 July, 2008. This was the fourth population census and the third housing census implemented in Vietnam since the nation was reunified in 1975. The Census aimed to collect basic data on the population and housing for the entire territory of the Socialist Republic of Vietnam, to provide data for research and analysis of population and housing developments nationally and for each locality. It responded to information needs for assessing implementation of socio-economic development plans covering the period 2001 to 2010, for developing the socio-economic development plans for 2011 to 2020 and for monitoring performance on Millennium Development Goals of the United Nations to which the Vietnamese Government is committed.

Geographic coverage

National

Analysis unit

Households Individuals Dwelling

Universe

The 2009 Population and Housing Census enumerated all Vietnamese regularly residing in the territory of the Socialist Republic of Vietnam at the reference point of 0:00 on 01 April, 2009; Vietnamese citizens given permission by the authorities to travel overseas and still within the authorized period; deaths (members of the household) that occurred between the first day of the Lunar Year of the Rat (07 February, 2008) to 31 March, 2009; and residential housing of the population.

Population and housing censuses were implemented simultaneously taking the household as the survey unit. The household could include one individual who eats and resides alone or a group of individuals who eat and reside together. For household with 2 persons and over, its members may or may not share a common budget; or be related by blood or not; or marital or adoptive relationship or not; or in combination of both. The household head was the main respondent. For information of which the head of household was unaware, the enumerator was required to directly interview the survey subject. For information on labour and employment, the enumerator was required to directly interview all respondents aged 15 and older; for questions on births, the enumerator was required to directly interview women in childbearing ages (from 15 to 49 years of age) to determine the responses. For information on housing, the enumerator was required to directly survey the household head and/or combine this with direct observation to determine the information to record in the forms.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Sample size In the 2009 Population and Housing Census, besides a full enumeration, some indicators were collected in a sample survey. The census sample survey was designed to: (1) expand survey contents; (2) improve survey quality, especially for sensitive and complicated questions; and (3) save on survey costs. To improve the efficiency and reliability of the census sample data, the sample size was 15% of the total population of the country. The sample of the census is a single-stage cluster sample design with stratification and systematic sample selection. Sample selection is implemented in two steps: Step 1, select the strata to determine the sample size for each district. Step 2, independently and systematically select from the sample frame of enumeration areas in each district to determine the specific enumeration areas in the sample.

The sample size of the two census sample surveys in 1989 and 1999 was 5% and 3% respectively, only representative at the provincial level; sample survey indicators covered fertility history of women aged 15-49 years and deaths in the household in the previous 12 months. In the 2009 Census, besides the above two indicators, many other indicators were also included in the census sample survey. The census sample survey provides data representative at the district level. When determining sample size and allocation, the frequency of events was taken into account for various indicators including birth and deaths in the 12 months prior to the survey, and the number of people unemployed in urban areas, etc.; efforts were also made to ensure the ability to compare results between districts within the same province/municipality and between provinces/ municipalities.

Stratification and sample allocation across strata To ensure representativeness of the sample for each district throughout the country and because the population size is not uniform across districts or provinces, the Central Steering Committee decided to allocate the sample directly to 682 out of 684 districts (excluding 2 island districts) throughout the country in 2 steps:

Step 1: Determine the sampling rate f(r) for 3 regions including: - Region 1: including 132 urban districts; - Region 2: including 294 delta and coastal rural districts; - Region 3: including 256 mountainous and island districts.

Step 2: Allocate the sample across districts in each region based on the sampling rates for each region as determined in Step 1 using the inverse sampling allocation method. Through applying to this allocation method, the number of sampling units in each small district is increased adequately to ensure representativeness. The formula used to calculate the sample rate for each district in each region is provided on page 22 of the Census Report (Part1) provided as external resources.

Sampling unit and method The sampling unit is the enumeration area that was ascertained in the step to delimit enumeration areas. The sampling frame is the list of all enumeration areas that was made following the order of the list of administrative units at the commune level within each district. In this way, the whole country has 682 sample frames (682 strata).

The provincial steering committee was responsible for selecting sample enumeration areas using systematic random sampling as follows: Step 1: Take the total of all enumeration areas in the district, divide by the number of enumeration areas needed in the sampleto determine the skip (k), which is calculated with precision up to 1 decimal point. Step 2: Select the first enumeration area (b, with b = k), corresponding to the first enumeration area to be selected. Each successive enumeration area to be selected will correspond to the order number: bi = b + i x k ; here i = 1, 2, 3…. Stopping when the number of enumeration areas needed has been selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires and survey materials were designed and tested three times before final approval.

Cleaning operations

The 2009 Population and Housing Census applied Intelligent Character Recognition technology/scanning technology for direct data entry from census forms to the computer to replace the traditional keyboard data entry that is commonly used in Vietnam at present. This is an advanced technology, and the first time it had been applied in a statistical survey in Vietnam. Preparatory work had to be done carefully and meticulously. Through organization of many workshops and 7 pilot applications with technical and financial assistance from the UNFPA, the new technology was mastered, and the Census Steering Committee Standing Committee approved use of this technology to process the entire results of the 2009 Population and Housing Census. The Government decided to allocate funds through the project on Modernization of the General Statistics Office using World Bank Loan funds to procure the scanning system equipment, software and technical assistance. The successful use of this technology will create a precedent for continued use of scanning technology in other statistical surveys

After checking and coding at the Provincial/municipal steering committee office, (both the complete census and the census sample survey), forms were checked and accepted then transferred for processing to one of three Statistical Computing Centres in Hanoi, Ho Chi Minh City and Da Nang. Data processing was implemented in only a few locations, following standard procedures and a fixed timeline. The steering committee at each level and processing centres fully implemented their assigned responsibilities, especially the checking, transmitting and maintenance of survey forms in good condition. The Central Steering Committee collaborated with the Statistical Computer Centres to set up a plan for processing and compiling results, setting up tabulation plans, interpreting and synthesizing output tables, and developing options for extrapolating from sample to population estimates.

The General Statistics Office completed the work of developing software applications and training using ReadSoft software (the one used in pilot testing), organized training on network management and training on systems and programs for logic checks and data editing, developed a data processing protocol, integrated these systems and completed data flow management programs. The General Statistics Office collaborated with the contractor, FPT, to develop software applications, train staff, testl the system and complete the programs using the new TIS and E-form software.

Compilation of results was implemented in 2 stages. In stage 1 data were compiled from the Census Sample Survey by the end of October, 2009, and in stage 2, data were compiled from the completed census forms, with work finalized in May 2010.

Sampling error estimates

Estimates from the Census sample survey were affected by two types of error: (1) non-sampling error, and (2) sampling error. Non-sampling error is the result of errors in implementation of data collection and processing such as visiting the

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia). Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093).From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for these months were: Census Religion (Module MCG): this module was asked on behalf of the Office for National Statistics. The questions aimed to help inform decisions on the final wording of questions in the 2011 Census and covered religion and citizenship. Census Religion (Module MCGb): this module, also asked on behalf of the Office for National Statistics, is a shortened version of Module MCG which ran in April and May 2009. Multi-stage stratified random sample Face-to-face interview

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Televisions (Module 177): this module was asked on behalf of the Department of National Heritage, to ascertain how many households have a television that did not work at the time and did not have another TV set that did work, and whether they intended to get the broken television set repaired in the next seven days after the interview took place. Test of census questions (Module 181): this module was asked on behalf of the Census Division of ONS and contained a self-completion form. Only respondents who were working at the time or had ever previously worked were asked to complete it. The purpose of this module was to test how well people are able to complete the proposed Census questions about occupation. Expectation of house price changes (Module 137): this module asks respondents' views on changes to house prices in the next year and next five years. Sun exposure (Module 178): this module was asked on behalf of the Department of Health and queried respondents' behaviour and opinions towards exposure to the sun. Fire safety (Module 33): this module covers fire safety and is asked in connection with Fire Safety Week. Questions assess awareness of fire risks and fire safety measures the respondent has taken. Marriage and Cohabitation (Module 179): this module was asked on behalf of the Lord Chancellor's Department and Oxford University, and queried respondents' opinions of various aspects of relationships. The module was asked only of respondents who were married for the first time and have children aged under 16, or were cohabiting and had never been married. Drinking (Module 180): this module was asked on behalf of the Health Education Authority (HEA) in England only. The module was updated for 1997 and contains new and different questions to those asked in 1996 and early 1997 (Module 113). The questions are asked of all adults aged 16 and over. Topics covered included alcohol consumption, drinking behaviour and intoxication. Contraception (Module 170): the Special Licence version of this module is held under SN 6475. Multi-stage stratified random sample Face-to-face interview

Abstract

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

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

Geographic coverage

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

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

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

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

Mode of data collection

Face-to-face

Research instrument

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

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

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

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for individual interview and children under five who were to be weighed and measured. Information was also collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, ownership of various consumer goods, and use of iodised salt. Finally, the Household Questionnaire was used to collect some rudimentary information about the extent of child labour.

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

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

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

Response rate

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

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

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

Sampling error estimates

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

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

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

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

Note: See detailed sampling error calculation in the APPENDIX B

Attitude of the German population to the census after census day, 31 May 1987. Political attitudes. Attitudes to deviant behavior and use of drugs.

Topics: 1. Political interest; satisfaction with democracy in the Federal Republic; satisfaction with current Federal Government; attitude to the census; receipt of a written request to fill out the questionnaire; assumed amount of non-participation in the census; attitude to the census in circle of friends and acquaintances; conversations about the census in the social surroundings and time of last conversation; noticed media reporting about the census; questions from the census that were reluctantly answered; attitude to punishment of census boycotters; knowledge of cases of refusal; assumed population participation in the census given voluntary participation; willingness to answer selected personal questions given voluntary participation; preference for census or providing data already available by government offices; assumed benefit or harm from discussion about the census in the media; attitude to calls for boycott; judgement on the success of the boycott movement; benefit of the census; self-assessment on a left-right continuum; most important elements of a democracy and characterization of democracy in the Federal Republic; party preference; violation of fundamental rights perceived personally or by persons of social surroundings; attitude to technology; personal concerns and attitude regarding misuse of personal census data; trust in observance of data protection; attitude to storing personal data; attitude to opinion polls (scale); willingness to participate in a microcensus survey; willingness to provide data from private sphere to friends, neighbors, census bureaus and scientific surveys; attitude to government statistics.

1. Attitude to selected illegal actions (scale); appropriate extent of punishment for such offences; law-abidingness; judgement on physical and psychological dangers of use of drugs (scale); attitude to legalization of hashish; personal familiarity with users of drugs; closer information on a drug addict in one´s circle of friends; excessive use of alcohol; traveling without a ticket; not paying entrance fees; trying hashish; areas in immediate vicinity of residence avoided at night.

Demography: month of birth of respondent; sex; marital status; number of children; ages of children (classified); religious denomination; frequency of church attendance; school education; vocational training; occupation; occupational position; employment; monthly gross income of respondent and household altogether; number of persons contributing to household income; size of household; position of respondent in household; characteristics of head of household; number of persons eligible to vote in household; persons in household who do not have German citizenship; self-assessment of social class; union membership of respondent and other members of household; possession of a telephone.

Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person introducing this intervention; attitude to census of persons additionally present during interview; presence of further persons in other rooms; willingness to cooperate and reliability of respondent.

Also encoded was: length of interview; date of interview; identification of interviewer; sex of interviewer; age of interviewer.

The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM(r) classification, census block group, and latitude-longitude. PRIZM(r) classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM(r) classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey.This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because of its higher spatial accuracy than other databases describing US Census geographies, including those provided by the US Census. This database includes data only for environmental satisfaction: Environment satisfaction is from question "#12 of the household telephone survey, How satisfied are you with the quality of the natural environment in your neighborhood (using a scale of zero through 10, where zero means you feel very dis-satisfied)? (If needed, the natural environment was defined as "trees, animals, grassy areas, streams, and open spaces")". The response is the percentage of respondents in that Prizm class who answered "7-10 on the scale, meaning they were satisfied". Neighborhood Rating is from question "#13 of the household telephone survey, On a scale of 0 through 10, with 0 being the worst and ten being the best, how would you rate your neighborhood as a place to live?" The response is the percentage of respondents in that Prizm class who answered "7-10" on the scale meaning that they think their neighborhood is a good place to live.Would you move away is from question "#14 of the household telephone survey, If you could, would you move away from your neighborhood?"The response is the percentage of respondents in that Prizm class who answered "No". Number of trees is from question "#17 of the household telephone survey, Approximately how many trees, total, would you estimate are visible from the windows in your residence.. a) none, b) less than 10, c) 10-50, d) 51-100, or e) over 100?"The response is the percentage of respondents in that Prizm class answering "d) 51-100 or e) over 100". This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Abstract

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

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

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

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

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

Cleaning operations

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

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

Response rate

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

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

Sampling error estimates

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

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

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

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

Abstract (en): This data collection is comprised of responses from two sets of survey questionnaires, the basic Current Population Survey (CPS) and a survey on the topic of voting and registration in the United States, which was administered as a supplement to the November 2008 CPS questionnaire. The Housing and Household Economic Statistics Division of the Census Bureau sponsored the supplemental questions for November.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment. Data from the CPS are provided for the week prior to the survey.The voting and registration supplement data are collected every two years to monitor trends in the voting and nonvoting behavior of United States citizens in terms of their different demographic and economic characteristics. The supplement was designed to be a proxy response supplement, meaning a single respondent could provide answers for all eligible household members. The supplement questions were asked of all persons who were both United States citizens and 18 years of age or older. The CPS instrument determined who was eligible for the voting and registration supplement through the use of check items that referred to basic CPS items, including age and citizenship.Respondents were queried on whether they were registered to vote in the November 4, 2008 election, main reasons for not being registered to vote, main reasons for not voting, whether they voted in person or by mail, and method used to register to vote. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. There is no supplement weight associated with the November 2008 supplement. Use the basic CPS weight, PWSSWGT, for tallying the supplement items. Please refer to the User Guide for additional information concerning the creation and use of this and other weight variables. All persons in the civilian noninstitutionalized population of the United States living in households. A multistage probability sample based on results of the decennial Census was used for the housing unit. computer-assisted personal interview (CAPI), computer-assisted telephone interview (CATI)Users are strongly encouraged to refer to the User Guide (produced by the Principal Investigators), which contains the questionnaire for the supplement, as well as additional detailed technical documentation regarding the study design, sampling frame used, and response rates.The universe statements for each variable are defined in either the basic or supplement record layout, which is located in Attachment 6 and 7, respectively, of the User Guide.ICPSR removed all FILLER and PADDING variables from the data. As a result, the column locations in any ICPSR-released data product (e.g., codebook and setup files) will have column locations that are not consistent with locations described in the User Guide.

Abstract

The 2011 Mauritius Housing & Population Census will be carried out by the Central Statistics Office in two distinct rounds: the Housing Census from 31 January 2011 to June 2011 followed by the Population Census from 20 June to 31 July 2011 in respect of all persons alive on the night of 3 - 4 July 2011. The main objective of the Housing and Population census is to provide up-to-date and disaggregated data on the housing conditions, the spatial distribution, and the demographic and socio-economic characteristics of the Mauritian population.

Geographic coverage

National

Analysis unit

• Household;
• Indivudual.

Universe

The Housing Census will enumerate all buildings, housing units, households, commercial and industrial establishments, hotels and boarding houses as well as fruit trees of bearing age on residential premises.

The Population Census will enumerate all persons present on census night in all households and communal establishments, as well as usual residents who are away on census night.

Housing and population enumerations will be conducted in the islands of Mauritius, Rodrigues and Agalega.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Census 2011, like the four previous ones, was taken in two distinct rounds: the Housing Census followed by the Population Census four months later. This enumeration procedure was adopted in order to obtain at the Housing Census a list of names and addresses of heads of households which served as frame for the Population Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

4.1 Questionnaire design The questionnaire type, format and contents were determined on the basis of the following factors:

Data to be collected Data collected were in line with UN recommendations and, in addition, catered for local data needs.

Method of enumeration For Census 2011, the questionnaires were completed by enumerators who carried out field interviews.

Data capture and processing techniques The office used scanning and recognition technology for census data capture directly from the questionnaires.

4.2 Contents of questionnaire The questionnaire contents were determined as follows: (i) The data needs of main stakeholders from Government Ministries and Departments were considered. As from 2008, heads of Government Ministries and Departments were invited via a circular letter to submit their requirements for demographic, social and economic data considered essential for administration, planning and policy-making and which could be collected at the census. Topics were retained after considering: - their usefulness to the country; - the cost for data collection and processing - where it is possible by other means to obtain satisfactory information more cheaply, the topic was not selected; and - their suitability for data collection at a Census - sensitive and controversial issues as well as questions that are too complicated or difficult for the average respondent to answer were avoided. (ii) The concepts and questions used for the previous census were examined for relevance and only those found relevant were kept. (iii) The latest “Principles and Recommendations for Population and Housing Censuses” were reviewed to determine whether to add questions or to modify existing questions. (iv) The questions thus arrived at were tested during a pilot census conducted in September 2010. In the light of observations made on the field, some changes were made to the wording and sequence of the questions and a final set of questions adopted. 4.2.1 The Housing Census questionnaire The Housing Census questionnaire covered all topics and items covered at Census 2000; some new items were added for the reasons given in the column “Remarks”.

The questionnaire was designed to cover 1 housing unit, up to two households, up to three planters and 1 commercial/industrial establishment, guest house or tourist residence. More than one questionnaire was used in other cases.

4.2.2 The Population Census questionnaire The 2011 Population Census questionnaire included the topics covered at the 2000 Population Census except that on income. Questions were added on National Identity number of each person as well as on residence for the reasons mentioned in the column “Remarks”.

4.3 Questionnaire layout and size The layout and design of response areas was done to ensure optimum conditions for data capture through scanning and recognition technology. The layout was also influenced by the cost (the number of pages had to be kept to a minimum to cut down on paper, printing and scanning costs) while at the same time ensuring ease of recording the answers on the field.

Cleaning operations

The quality of information collected depends not only on the training of field workers, but also on the day-to-day control and supervision of the fieldwork. Supervisors had to accompany each of their Enumerators in the first visits to ensure that interviews were done according to instructions given and that all concepts were clearly understood. Surprise and pre-arranged field checks as well as re-interviews also helped to increase the reliability of the information collected. Furthermore, Supervisors had to check all completed questionnaires at the early stage of enumeration and later a sample of the completed questionnaires to ensure that the quality of work was satisfactory. Meetings were held regularly to take stock of the field situation and to solve problems met on the field.

All supervisory staff had to record their field activities in provided diaries. The day-today record outlined the activities carried out, the dates and the places at which the activities were carried out, problems encountered and remedial actions taken. The day-to-day recording of activities allowed supervisory staff to follow the progress of work and to assess the performance of each and every staff working under their supervision. Furthermore, it ensured that supervisory control prevailed all along the fieldwork.

Abstract

In 2014 World Bank, with the help of a local survey company, conducted a unique survey in the Kyrgyz Republic surveying 1,080 households in all oblasts (regions) of the country on experience of encountering with corruption practices and attitudes toward social assistance.

The survey is representative at three strata levels: urban, rural and capital city. The questionnaire replicated the set of questions from the official household survey, which allowed to estimate the consumption model and impute the welfare status of the household (i.e. impute the value of per capita consumption expenditure) based on a set of non-monetary/non-consumption questions. As a result it was possible to infer on distributional impact of (petty) corruption practices across different groups of households. Apart from this, the survey collected rich set of data on perception of corruption and household views on corruption practices by various public institutions. The survey greatly assisted informing the anti-corruption strategy and World Bank's dialogue in the country.

Geographic coverage

National

Analysis unit

Respondents aged 16 and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary target population is all regular (non-institutional) households in the Kyrgyz Republic. Other target populations are all population oldest 16 years living in non-institutional households. The survey population is identical to the target population; the survey covers all areas within the national borders.

The primary sampling frame will be the list of census enumeration areas (EA) from the Census 2009. There are in all 13 297 enumeration areas in the Republic. Many of the rural EAs are formed around settlements (villages) so the EA coincides with the settlement. Larger settlements contain two or more EAs.

For each EA there is information on total number of people (by sex) and total number of households .There is also administrative information on urban/rural classification, municipality, district and oblast as well as a sketch map of the area. The census maps are kept at the municipality offices. There have been no changes in boundaries between administrative units (municipality, district, and region) since the census, but 50 EAs have been reclassified from urban to rural. The frame has been updated accordingly. The Kyrgyz project employs a stratified two stage design.

The first stage of sampling entails sampling of areas. In the second stage a sample of households are selected in each selected area. The census enumeration areas serve as first stage sampling units - Primary Sampling Units (PSU). Within selected PSUs a sample of households is drawn.

The survey domains are the eight administrative regions plus Bishkek City. It was decided to stratify the sample on survey domain by urban/rural area and Bishkek City. There are therefore 3 strata in all. It was discussed if a deeper stratification- further stratification within region - would give further gains in precision of the estimates. It was concluded that the gains would be small so no further stratification was done. There is, however, an implicit geographical stratification within each province. This is achieved by a geographical ordering of the PSUs and systematic sampling of PSUs in the first stage of sampling.

Number of Sample Households per Cluster

The project had a cluster size of 12households. This is a rather small cluster size compared to what is used in many other surveys focusing on demographic indicators. With a cluster size of 10 households altogether 108 PSUs would be needed to achieve a sample of 1080 households. A larger cluster size than 10 would mean that fewer PSUs than 108are needed. Consequently, the field work costs per household would be lower. On the other hand, the standard errors would be larger. To find out the theoretically "optimum" cluster size - the cluster size that gives the best precision per unit of cost - detailed data on field work costs would be needed. These data are not at hand but some crude calculations could still be done using "guesstimates" on average time for transports between PSUs, time for listing of households in sample PSUs and time for interview per household. Based on the calculations described above it was decided to increase the cluster size from 10to 12 households. This size may well differ from the theoretical optimum value but it is suitable from a practical field work point of view. The total sample size is1080 households. So, the number of PSUs will be 1080/12= 90.

Sampling of PSUs

The PSUs are selected by systematic PPS sampling (PPS= sampling with probabilities proportionate to size). The PSUs are ordered in geographical sequence within the stratum before the selection of PSUs is done. The size measures are the number of households in the PSU from the Census 2009. It was discussed within the sampling group whether there was a need for adjusting the size measures of some PSUs. This should be done in areas where it is known that substantial changes have taken place since the census (e.g. new large scale housing projects or clearance of squatter areas). The conclusion of the discussion was that updating of size measures should not be done. The opinion was that there should be rather few cases of radical population changes and also, that it will be difficult/costly to obtain updated information at the PSU level. The sampling of PSUs will be done in Excel by a standard procedure which is used for all household surveys.

Sampling of Households

For each selected PSU, the starting points will be defined by regional supervisors. Big cities are divided into several territorial units, these units placed in the program Excel, and then the program will randomly select starting points. In the rural area starting point is also determined by supervisors. The interviewer reaches selected from the sample village and then interviewer describes the layout of the streets supervisor and administrative buildings (the number of streets, crossing the street, the number of administrative buildings). This all is entered in the program Excel and then the program will randomly select starting point for this village. The interviewer has no right to select the starting point, or change it.

Starting from the given address/point, an interviewer will follow strict rules to select a household and a respondent within selected household. The random route method using the right-hand rule is used with the predefined interval of three to select the household (counting each third household, excluding the starting point). Never move on the left side! In the deadlock - Interviewers cover only the right side of the street. In apartment building interviewers begin to move from the top floor down in a clockwise direction, also adhere to step 3.

Each third household is considered as main household, where up to three contacts must be attempted at different times of the day, days of the week, and the weekend within the fieldwork period to conduct a successful interview. In areas where the interviewer will not be able to return on a different day, the interviewer will make attempts with at least a two-hour gap between each attempt before substituting the household.

If the interviewer cannot obtain an interview at the main sample household, the interviewer selects the household to the immediate right of the main household as the first substitute. In the event that the attempt at the substitute household also fails, then the interviewer selects the house immediately to the left of the initial/main household as the second substitute. In the event that an interviewer fails to obtain an interview at all three households, the interviewer selects another main household continuing with the same interval and numbering sequence of questionnaires can be saved.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed is such way to replicate the set of questions from official household survey, which eventually allowed to impute the welfare status of household (impute the value of per capita consumption expenditure) based on set of non-monetary/non consumption questions.