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.

Abstract

The Statistical and Forecasting Service has been entrusted with the production of the AC 2010. (SSP) which is the central statistical department of the Ministry in charge of agriculture, (MAAPRAT) the central department is in charge of the design of the operation, the drafting of the questionnaire and instructions, the training of regional services, the final quality control of the data collected and of the first publication of the results. The SSP has relied on its specialised decentralised levels, the services regional statistics (NUTS2) of statistical and economic information (SRISE). The threshold definition of agricultural holding applied has been the same since 1955, and corresponds exactly to the one proposed by the European regulation. The geographical area is the whole of France; for the DOM the territories of Saint-Martin and Saint-Barthélemy are now excluded, Mayotte is not yet included.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit in the AC 2010 was the agricultural holding, defined as an economic unit that participates in agricultural production and meets the following criteria: · it has an agricultural activity either of production, or of maintenance of the lands in good agricultural and environmental

Kind of data

Census/enumeration data [cen]

Sampling procedure

a. Frame The basic list of agricultural holdings was built using the SSP farm register, the SIRENE register (business register), the list of farmers who had applied for aid (area declarations),' and some additional sources for beekeeping, olive oil, aromatic plants. The holding lists were checked at local level by communal commissions.

b. Complete and/or sample enumeration method(s) The AC and SAPM were conducted using complete enumeration.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Three questionnaires were used: one for France in Europe (including questions of regional interest) and two for France's overseas territories: one for Guadeloupe, Martinique and Reunion and another for Guyana. The census covered all 16 core items recommended in the WCA 2010. ie.

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

Cleaning operations

a. DATA PROCESSING AND ARCHIVING The CAPI interface included controls to ensure that there were responses to all questions. In addition, interactive range and consistency checks were included for each variable so that corrections could be made by the enumerator during the interview. Further edits and imputations were completed at the central office where the census validation and tabulation was completed. To ensure that the list of holdings was complete, several tests were conducted at the end of collection. All available administrative sources were used to verify that existing holdings had been identified and included. The key databases and registers used included that for EU agriculture aid applications, the national database of bovine identification, the computerized vineyard register, organic producer records, and some local registers for small productions. The data, after validation, were archived on secured servers.

b. CENSUS DATA QUALITY To assess the quality of field data collection, completeness checks and feedback were performed at the end of field data collection operation, from March to June 2011. Data checking began during the collection phase on the farmer's premises. It then continued throughout the processing chain. A special effort was made to check the AC's coverage by using the administrative data available. The nonresponse rate was of only 0.96 percent, and the missing data were imputed using the hot deck method.

Data appraisal

The first provisional census results were disseminated in September 2011, ten months after the end of the reference period. The main final results were made available at the end of February 2012, 16 months after the end of the reference period. The AC 2010 results were disseminated online and are available on the SSP website.9 The "ADEL" tool allows web users to build their own tables.

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

The primary objective of SASAS is to design, develop and implement a conceptually and methodologically robust study of changing social attitudes and values in South Africa to be able to carefully and consistently monitor and explain changes in attitudes amongst various socio-demographic groupings. The SASAS explores a wide range of value changes, including the distribution and shape of racial attitudes and aspirations, attitudes towards democratic and constitutional issues, and the redistribution of resources and power. Moreover, there is also an explicit interest in mapping changing attitudes towards some of the moral issues that confront and are fiercely debated in South Africa, such as gender issues, AIDS, crime and punishment, governance, and service delivery. The SASAS is intended to provide a unique long-term account of the social fabric of modern South Africa, and of how its changing political and institutional structures interact over time with changing social attitudes and values.

Geographic coverage

The survey has national coverage

Analysis unit

The units of analysis in the study are households and individuals

Universe

The population under investigation includes adults aged 16 and older in private households in South Africa

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for the survey is the Human Sciences Research Council’s (HSRC) Master Sample, which was designed in 2002 and consists of 1000 primary sampling units (PSUs). The 2001 population census enumerator areas (EAs) were used as PSUs. These PSUs were drawn, with probability proportional to size, from a pre-census 2001 list of EAs provided by Statistics South Africa. The Master Sample excludes special institutions (such as hospitals, military camps, old age homes, school and university hostels), recreational areas, industrial areas and vacant EAs. It therefore focuses on dwelling units or visiting points as secondary sampling units, which have been defined as ‘separate (non-vacant) residential stands, addresses, structures, flats, homesteads. As the basis of the 2003 SASAS round of interviewing, a sub-sample of 500 PSUs was drawn from the HSRC’s Master Sample. Three explicit stratification variables were used, namely province, geographic type and majority population group. Number of units: Questionnaire 1: 2 497 cases realised from 3 500 addresses; questionnaire 2: 2 483 cases realised from 3 500 addresses; combined : 4980 cases

Mode of data collection

Face-to-face [f2f]

Research instrument

To accommodate the wide variety of topics that was included in the 2004 survey, two questionnaires were administered simultaneously. Apart from the standard set of demographic and background variables, each version of the questionnaire contained a harmonised core module that will remain constant from round to round, with the aim of monitoring change and continuity in a variety of socio-economic and socio-political variables. In addition, a number of themes will be accommodated on a rotational basis. This rotating element of the survey consists of two or more topic-specific modules in each round of interviewing and is directed at measuring a range of policy and academic concerns and issues that require more detailed examination at a specific point in time than the multi-topic core module would permit.

In respect of the two SASAS questionnaires, the questions contained in the core module (demographics and core thematic issues) were asked of all 7 000 respondents, while the remaining rotating modules were asked of a half sample of approximately 3 500 respondents each. The two different versions of the questionnaire were administered concurrently in each of the chosen sampling areas. Fieldworkers were required to complete a paper-based instrument while interviews were conducted face-to-face. Questions for the core module were asked of both samples (3 500 respondents each – 7 000) of which 5 583 were realised.

ISSP Module: The International Social Survey Programme (ISSP) is run by a group of research organisations, each of which undertakes to field annually an agreed module of questions on a chosen topic area. SASAS 2003 represents the formalisation of South Africa's inclusion in the ISSP, the intention being to include the module in one of the SASAS questionnaires in each round of interviewing. Each module is chosen for repetition at intervals to allow comparisons both between countries (membership currently stands at 40) and over time. In 2003, the chosen subject was national identity, and the module was carried in version 2 of the questionnaire (Qs.152-203).

The standard questionnaires dealt with democracy, identity, public services, social values, crime, voting, demographics, families and family authority The rotating modules in the 2004 survey covered: Questionnaire 1: Poverty, environment, democracy (part 2) Questionnaire 2: ISSP module (citizenship), democracy (part 2)

Description: The FSB used a multidimensional approach to financial literacy, which centres on four principal domains: namely, day-to-day money management, financial planning, choosing appropriate products, and financial knowledge and understanding. The questionnaire was structured in a way as to capture these domains. Respondents had to complete all questions in all sections. The data set for dissemination contains 2972 cases and 897 variables. Abstract: SASAS represents a notable tool for monitoring evolving social, economic and political values among South Africans, but it also demonstrates promising utility as an anticipatory, or predictive, mechanism that can inform decision- and policy-making processes. Due to various requests from government departments and other organisations, the HSRC has made a capacity available for external organisations to participate in the survey by purchasing questions in the survey (the so called client questionnaire). In 2011 the FSB purchased a full module of questions in the SASAS survey, attempting to determine a financial literacy baseline for South Africa. The SASAS 2011 round was designed to yield a representative sample of 3 500 individuals aged 16 and older in households which are geographically spread across the country's nine provinces. Each SASAS round of interviewing consists of a sample of 500 Population Census enumeration areas (EAs) as primary sampling units, stratified by province, geographical sub-type and majority population group. Face-to-face interview National Population: Adults (aged 16 and older). The sampling frame used for the survey is based on the 2001 census and enumerator areas(EAs) were used as the primary sampling unit. Estimates of the population numbers for various categories of the census variables were obtained per EA. SASAS has been designed to yield a representative sample of 3500 adult South African citizens aged 16 and older (with no upper age limit), in households geographically spread across the country's nine provinces. The sampling frame used for the survey was based on the 2011 census and a set of small area layers (SALs). Estimates of the population numbers for various categories of the census variables were obtained per SAL. In this sampling frame special institutions (such as hospitals, military camps, old age homes, schools and university hostels), recreational areas, industrial areas and vacant SALs were excluded prior to the drawing of the sample. Small area layers (SALs) were used as primary sampling units and the estimated number of dwelling units (taken as visiting points) in the SALs as secondary sampling units. In the first sampling stage the primary sampling units (SALs) were drawn with probability proportional to size, using the estimated number of dwelling units in an SAL as measure of size. The dwelling units as secondary sampling units were defined as "separate (non-vacant) residential stands, addresses, structures, flats, homesteads, etc." In the second sampling stage a predetermined number of individual dwelling units (or visiting points) were drawn with equal probability in each of the drawn dwelling units. Finally, in the third sampling stage a person was drawn with equal probability from all 16 year and older persons in the drawn dwelling units. Three explicit stratification variables were used, namely province, geographic type and majority population group. As stated earlier, within each stratum, the allocated number of primary sampling units (which could differ between different strata) was drawn using proportional to size probability sampling with the estimated number of dwelling units in the primary sampling units as measure of size. In each of these drawn primary sampling units, seven dwelling units were drawn. This resulted in a sample of 3500 individuals. A list of the 500 drawn SALs were given to geographic information specialists (GIS) and maps were then created for each of the 500 areas, indicating certain navigational beacons such as schools, roads churches etc. Selection of individuals: For each of the SASAS samples interviewers visited each visiting point drawn in the SALs (PSU) and listed all eligible persons for inclusion in the sample, that is all persons currently aged 16 years or older and resident at the selected visiting point. The interviewer then selected one respondent using a random selection procedure based on a Kish grid.

Abstract

The Statistical and Forecasting Service has been entrusted with the production of the AC 2010. (SSP) which is the central statistical department of the Ministry in charge of agriculture, (MAAPRAT) the central department is in charge of the design of the operation, the drafting of the questionnaire and instructions, the training of regional services, the final quality control of the data collected and of the first publication of the results. The SSP has relied on its specialised decentralised levels, the services regional statistics (NUTS2) of statistical and economic information (SRISE). The threshold definition of agricultural holding applied has been the same since 1955, and corresponds exactly to the one proposed by the European regulation. The geographical area is the whole of France; for the DOM the territories of Saint-Martin and Saint-Barthélemy are now excluded, Mayotte is not yet included.

For statistical purposes, agricultural censuses in French territories (French Guyana, Guadeloupe, Reunion and Martinique) are recorded separately in the World Census of Agriculture Database. The census results are presented for all of France.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit in the AC 2010 was the agricultural holding, defined as an economic unit that participates in agricultural production and meets the following criteria: · it has an agricultural activity either of production, or of maintenance of the lands in good agricultural and environmental

Kind of data

Census/enumeration data [cen]

Sampling procedure

a. Frame The basic list of agricultural holdings was built using the SSP farm register, the SIRENE register (business register), the list of farmers who had applied for aid (area declarations),' and some additional sources for beekeeping, olive oil, aromatic plants. The holding lists were checked at local level by communal commissions.

b. Complete and/or sample enumeration method(s) The AC and SAPM were conducted using complete enumeration.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Three questionnaires were used: one for France in Europe (including questions of regional interest) and two for France's overseas territories: one for Guadeloupe, Martinique and Reunion and another for Guyana. The census covered all 16 core items recommended in the WCA 2010. ie.

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

Cleaning operations

a. DATA PROCESSING AND ARCHIVING The CAPI interface included controls to ensure that there were responses to all questions. In addition, interactive range and consistency checks were included for each variable so that corrections could be made by the enumerator during the interview. Further edits and imputations were completed at the central office where the census validation and tabulation was completed. To ensure that the list of holdings was complete, several tests were conducted at the end of collection. All available administrative sources were used to verify that existing holdings had been identified and included. The key databases and registers used included that for EU agriculture aid applications, the national database of bovine identification, the computerized vineyard register, organic producer records, and some local registers for small productions. The data, after validation, were archived on secured servers.

b. CENSUS DATA QUALITY To assess the quality of field data collection, completeness checks and feedback were performed at the end of field data collection operation, from March to June 2011. Data checking began during the collection phase on the farmer's premises. It then continued throughout the processing chain. A special effort was made to check the AC's coverage by using the administrative data available. The nonresponse rate was of only 0.96 percent, and the missing data were imputed using the hot deck method.

Data appraisal

The first provisional census results were disseminated in September 2011, ten months after the end of the reference period. The main final results were made available at the end of February 2012, 16 months after the end of the reference period. The AC 2010 results were disseminated online and are available on the SSP website.9 The "ADEL" tool allows web users to build their own tables.

The first table with main results shows the total number and area of holdings broken down by continental France, on one hand, and its overseas territories, on the other. See metadata review tables in external materials.

Abstract

The 2010 Population Census has been designed to meet various data needs, including as (1) the basis for updating population data bases up to the lowest level of administrative unit (village); (2) valuable input in monitoring the progress for achieving the Millennium Development Goals (MDGs); (3) the basis for preparing small area statistics; (4) basis for preparing population projection; (5) the basic data in developing sampling frame for various surveys conducted between 2010-2020.

During the 2010 Population Census it is estimated that the population of Indonesia would be around 232 million people who live in about 65 million households. Considering the huge number of population to be recorded the field enumeration will require more than 650.00 field workers, which consist about 450.000 enumerators, 150.000 team coordinators, and 15.000 field coordinators. Data collection is designed to be undertaken in groups, each group (team) consist of four persons, i.e. three numerators and one team coordinator. All field workers would have undertaken a three-day training before hand.

The peak of census operations will be during the months of May 2010 where field enumeration will be taking place simultaneously overall the geographical area of Indonesia. May 15 will be designated as the Census Date of the 2010 Population Census, therefore on the 15 of May 2010 the homeless and nomadic population will be canvassing.

Updating population data is a very crucial issue in the upcoming population census, in the sense that since the implementation of decentralization in 2001 the number of administrative units in the regions (province, district, sub district, and village) have been increasing tremendously, such that statistical measures could not appropriately follows the changes. Prior to decentralization the number of provinces was 27, districts 297, sub districts 4.200, and villages about 65.000. At present the number of provinces is 33, districts 497, sub districts about 7.000, and villages about 75.000.

Geographic coverage

National

Analysis unit

• Individuals;
• Households.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

In the modern context there is always an increasing demand for data and information, and this is not an exception for the census as well. A census being a huge national undertaking incurring substantial amount of money, while the resources are always constrained and limited. The choice of topic to be covered in a census mainly depends upon the user needs. However, as society becomes complex the demand of population data for development plans is not only increasing but the level of such information is switching to smaller administrative levels, while census being a complex and large operation has its own limitations in meeting all the demands of data users. Another main consideration for determining census topic is to maintain comparability and continuity of the census information.

There are three kind of questionnaires will be used in the 2010 Population Census, namely C1 (42 questions) for enumerate regular household who live in the areas that are covered in the mapping, C2 (14 questions) for enumerate population who live in the areas which are not included in the mapping such as remote areas, Indonesia corps diplomatic who live abroad and L2 (number and sex) for enumerate homeless people, boat people, and tribes.

The questionnaires hopefully can accommodate the data required for the compilations of MDG Indicators, which is essential for national policy making and monitoring. The census questionnaires are presently being developed taking into considerations of the relevant United Nation recommendations as well as the suitability of the items collected to meet local conditions.

In the past population censuses, data were collected basically by face-to-face interviews, where enumerators visited all households to interview persons therein one by one. In light of the changing lifestyle of big cities people and advancement of technology, new and additional means for data collection from the households will be introduced in the 2010 Population Census. Under the new multi-modal data collection approach, e-census on the Internet and self-enumeration will be rolled out, along with the traditional “interviewer” method.

Cleaning operations

The processing of data collected in a census constitutes one of the most important and challenging activities that have to be undertaken efficiently and expeditiously in order to justify the immense resources invested in a census. This activity entailed several processes: manual editing of the questionnaires after enumeration, data capture, data cleaning and validation, and finally tabulation. Intelligence character recognition (ICR) technology will be employed for data capture.

Government’s commitment to provide provisional results within two and half months after enumeration and final results within another six months greatly influenced the strategies and actions adopted at every stage of data processing in order to adhere to the commitment.

Abstract

Central Bureau of Statistics (BPS) has been collecting data since 1980 Podes conjunction with the implementation of the Population Census 1980 and which last in 2005, before the implementation of the 2006 Economic Census. PODES data collection is done 3 times in the past 10 years, which is coincide with the implementation of the Population Census, Census of Agriculture, and Economic Census. However, data collection Podes in 1994 and 1995 had made relating to the Presidential program Underdeveloped Villages (IDT). Since 2008, Podes planned data collection activities will be conducted independently of the various census activities.

Podes 2008 experienced some important changes for improvement as well as increase the benefits to consumers of data, especially local governments in planning for regional development. Proposed changes is the addition of the questionnaire Supplements District (Podes08-district) and Supplements District / City (Podes08-Kab/Kota). With the additional questionnaire this then expected which the data collected would be more accurate. Some questions may not be accurate or rare occurrence at the next village questionnaire asked on the questionnaire Supplements Supplements District and Regency / City. In addition it also added some new questions such as the pioneering commercial airfield, terminal passenger automobiles or more, river crossing, and a few other questions.

Geographic coverage

Nasional coverage, representatif to village level.

Analysis unit

Village

Universe

Village

Kind of data

Census/enumeration data

Sampling procedure

Data collection is done Podes 2008 census (complete enumeration). Field enumeration conducted through direct interviews by enumerators (PCL) with the village chief / headman, designated staff or other relevant sources. 2008 survey results Podes village / urban made two (2) copies of the red and blue. One double red should be sent to the BPS Regency / City for processing and 1 (one) of the double blue is in the Archives village / urban. Enumerators (PCL) is a district coordinator Statistics (KSK) or other officer (statistically partners) who have been trained that number is adjusted to the needs / field conditions and precedence for them to master their working areas. A PCL will record approximately 7 villages. While the staff BPS Regency / City served as the supervisors / examiners (PML). Subsequently a PML oversees approximately 3 (three) PCL. Officer Podes08-district record is KSK or staff BPS Regency / City, while on duty to record Podes08-Kab/Kota is staff BPS Regency / City. Supervision of both types of data collection officer is Head of Social Statistics or staff BPS Regency / City.

Mode of data collection

Face-to-face [f2f]

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

The Statistical and Forecasting Service has been entrusted with the production of the AC 2010. (SSP) which is the central statistical department of the Ministry in charge of agriculture, (MAAPRAT) the central department is in charge of the design of the operation, the drafting of the questionnaire and instructions, the training of regional services, the final quality control of the data collected and of the first publication of the results. The SSP has relied on its specialised decentralised levels, the services regional statistics (NUTS2) of statistical and economic information (SRISE). The threshold definition of agricultural holding applied has been the same since 1955, and corresponds exactly to the one proposed by the European regulation. The geographical area is the whole of France; for the DOM the territories of Saint-Martin and Saint-Barthélemy are now excluded, Mayotte is not yet included.

For statistical purposes, agricultural censuses in French territories (French Guyana, Guadeloupe, Reunion and Martinique) are recorded separately in the World Census of Agriculture Database. The census results are presented for all of France.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit in the AC 2010 was the agricultural holding, defined as an economic unit that participates in agricultural production and meets the following criteria: · it has an agricultural activity either of production, or of maintenance of the lands in good agricultural and environmental

Kind of data

Census/enumeration data [cen]

Sampling procedure

a. Frame The basic list of agricultural holdings was built using the SSP farm register, the SIRENE register (business register), the list of farmers who had applied for aid (area declarations),' and some additional sources for beekeeping, olive oil, aromatic plants. The holding lists were checked at local level by communal commissions.

b. Complete and/or sample enumeration method(s) The AC and SAPM were conducted using complete enumeration.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Three questionnaires were used: one for France in Europe (including questions of regional interest) and two for France's overseas territories: one for Guadeloupe, Martinique and Reunion and another for Guyana. The census covered all 16 core items recommended in the WCA 2010. ie.

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

Cleaning operations

a. DATA PROCESSING AND ARCHIVING The CAPI interface included controls to ensure that there were responses to all questions. In addition, interactive range and consistency checks were included for each variable so that corrections could be made by the enumerator during the interview. Further edits and imputations were completed at the central office where the census validation and tabulation was completed. To ensure that the list of holdings was complete, several tests were conducted at the end of collection. All available administrative sources were used to verify that existing holdings had been identified and included. The key databases and registers used included that for EU agriculture aid applications, the national database of bovine identification, the computerized vineyard register, organic producer records, and some local registers for small productions. The data, after validation, were archived on secured servers.

b. CENSUS DATA QUALITY To assess the quality of field data collection, completeness checks and feedback were performed at the end of field data collection operation, from March to June 2011. Data checking began during the collection phase on the farmer's premises. It then continued throughout the processing chain. A special effort was made to check the AC's coverage by using the administrative data available. The nonresponse rate was of only 0.96 percent, and the missing data were imputed using the hot deck method.

Data appraisal

The first provisional census results were disseminated in September 2011, ten months after the end of the reference period. The main final results were made available at the end of February 2012, 16 months after the end of the reference period. The AC 2010 results were disseminated online and are available on the SSP website.9 The "ADEL" tool allows web users to build their own tables.

The first table with main results shows the total number and area of holdings broken down by continental France, on one hand, and its overseas territories, on the other. See metadata review tables in external materials.

Abstract

The National Sample Census of Agriculture (NCA) of Nepal 2001/02, conducted by the Central Bureau of Statistics is the most recent census of agriculture in His Majestic Government, Nepal. The first census in this country was conducted in 1961/62. Since then, the Census of Agriculture has been conducted decennially: 1971/72, 1981/82 and 1991/92.

The 2001/02 NCA was undertaken in two phases. The first phase involved the complete enumeration of all agricultural holdings in the country including the area of the holding and livestock number. The enumeration of all the holdings was an integral activity of the first phase of the Census of Population 2001, which undertook the listing operation from May 14-28, 2001. Some questions on agricultural activities were asked to identify the agricultural holding. The second phase of the 2001/02 NCA was the selection and enumeration of sample holdings to widen the scope of the census from January to June 2002. Data on agricultural crops gathered refer to calendar year 2001 while the livestock and poultry population refers at the time of enumeration, from January to June 2002.

The main objective of the census of agriculture of Nepal is to publish data at district level on the following: 1. Structure and characteristics of the holding such as size, agricultural land use, land tenure, land fragmentation, area planted to crops, number of livestock, and others; 2. To provide benchmark data for improving the reliability of estimates from current agricultural survey; and, 3. To provide basic data for national, ecological belts and development regions levels for national as well as sub-national policy, planning and decision making purposes.

Geographic coverage

National Coverage

Analysis unit

Agricultural holdings

Universe

All agricultural households having a minimum specified agricultural land area operated by holding (for hill and mountain region 4 anna and 8 dhure in terai) or having a specified minimum number of livestock or poultry.

Agricultural activities undertaken by government organizations, businesses like corporations and other juridical persons were not covered by the NCA.

Kind of data

Census/enumeration data [cen]

Sampling procedure

A two-stage stratified sampling was employed in the selection of the samples for enumeration to obtain the characteristics of the holdings for the 2001/02 NCA. This design is similar to that of the 1991/92 sampling design, which is a self-weighting sample.

The listing of the wards in each district with the summarized data of the number of holdings and area was used to form enumeration areas (EA's). However, wards containing less than 30 holdings were combined to form one EA. The EAs in each district were stratified according to the number of holdings enumerated, arranged from the highest to the lowest.

There are some VDCs (Village Development Committees) that were not covered by the listing operations or census enumeration during the Census of Population 2001 involving 12 districts. However, some estimates of the number of households and population were prepared by the Population Division based on the census listing or some independent sources of information, in the absence of the listing of households. The 12 districts are: Jhapa and Siraha districts both in Eastern Tarai; Surkhet and Salyan districts in Midwestern Hill; Sindhupalchok and Dolakha districts in Central Mountain; Sinduli district in Central Hill; Dolpa, Jumla, Kalitkot, and Mugu districts all in Midwestern Mountain; and Bajura district in Far-Western Mountain.

The first stage of sample selection involved the primary sampling units (PSUs), where sample enumeration areas (EAs) were selected with probability proportional to size (PPS). The measure of size is the number of holdings enumerated in the EAs during the Census of Population 2001 listing operations.

To measure the importance of each district, the total area under 8 major crops was determined (paddy, wheat, maize, millet, barley, sugarcane, oilseed and potato). Districts were stratified into four groups according to this criterion. Group I represented the 10 least important districts; Group II, the next 15 important districts and Group III, the next 25 important districts and Group IV, the 25 most important districts. The number of selected EAs per district in each group follows: Group I - 50 EAs per district (total of 450 EAs because one district, specifically Manang district was taken as a certainty sample district) Group II - 60 EAs per district (total of 900 EAs) Group III - 70 EAs per district (total of 1,750 EAs) Group IV- 80 EAs per district (total of 2000 EAs).

The second stage of sample selection involved the selection of sample holdings systematically in each sample EA. Before the sample selection was done, a listing of holdings in each sample PSU was conducted to update the listing during the Population Census. The target number of holdings for enumeration in each sample EA was 25.

The Census of Agriculture sample was designed to be self-weighting within each district, i.e. all holdings within a district have the same chance of being included in the sample. Approximately 5,100 enumeration areas were selected in the 74 districts and about 125,000 agricultural holdings were selected for enumeration. One district was completely covered in the second phase of the census of agriculture because of the few number of enumeration areas and holdings. This is the district of Manang. The detailed stratification scheme done on the districts, the sampling procedures and the estimation of parameters for each district are found in the technical report, which is one of the series of reports prepared for the 2001/02 NCA.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The data were subjected to the following editing processes: 1. Manual editing and coding were done at the head office after collecting the filled questionnaires. 2. Completeness check after data entry done by a completeness checking computer program. 3. Machine editing by machine editing program.

Data appraisal

A pilot survey was conducted one year ago i.e. in 2000. Training for district officers and supervisors was held in the centre and training for the field supervisors and enumerators was held in districts at the beginning of the field work. On the average, one hour is taken for filling the questionnaire i.e. schedule. Nepali national language was used for conducting the interviews.

Abstract

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

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women age 15-49, all men age 15-59, and all children age 0-5 years who are usual members of the selected households or who spent the night before the survey in the selected households.

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

Cleaning operations

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

Response rate

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

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

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

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2018 Zambia Demographic and Health Survey (ZDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2018 ZDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

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

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

Data appraisal

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

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