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  <docDscr>
    <citation>
      <titlStmt>
        <titl>
          rw-nisr-2012-pes-v1
        </titl>
        <IDNo>
          ddi-rwa-nisr-rpes-2012-v1
        </IDNo>
      </titlStmt>
      <rspStmt>
        <othId role="Study documentation" affiliation="Ministry of Finance and Economic Planning">
          <p>
            National Institute of Statistics of Rwanda
          </p>
        </othId>
      </rspStmt>
      <prodStmt>
        <producer abbr="NISR" affiliation="Ministry of Finance and Economic Planning" role="Stady description">
          National institute of Statistics of Rwanda
        </producer>
        <prodDate date="2015-03-27">
          2015-03-27
        </prodDate>
        <software version="4.0.9" date="2013-04-23">
          Nesstar Publisher
        </software>
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      <verStmt>
        <version>
          v1
        </version>
      </verStmt>
    </citation>
  </docDscr>
  <stdyDscr>
    <citation>
      <titlStmt>
        <titl>
          Rwanda Post Enumeration Survey 2012
        </titl>
        <altTitl>
          RPES 2012
        </altTitl>
        <IDNo>
          rwa-nisr-rpes-2012-v1
        </IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty affiliation="Ministry of Finance and Economic Planning">
          National Institute of Statistics of Rwanda
        </AuthEnty>
        <othId role="Awareness and mobilisation" affiliation="Ministry of Local Government">
          <p>
            Local Government
          </p>
        </othId>
      </rspStmt>
      <prodStmt>
        <producer/>
        <producer/>
        <producer/>
        <copyright>
          (c) 2014, National Institute of Statistics of Rwanda
        </copyright>
        <software version="4.0.9" date="2013-04-23">
          Nesstar Publisher
        </software>
        <fundAg abbr="GoR" role="Financial support">
          Government of Rwanda
        </fundAg>
        <fundAg abbr="One UN" role="Financial assistance">
          One UN
        </fundAg>
        <fundAg abbr="UNFPA" role="Financial assistance">
          United Nations Population Fund
        </fundAg>
        <fundAg abbr="UNICEF" role="Financial assistance">
          United Nations Children's Fund
        </fundAg>
        <fundAg role="Financial assistance">
          UKaid
        </fundAg>
        <fundAg abbr="WB" role="Financial assistance">
          World Bank
        </fundAg>
        <fundAg abbr="EU" role="Financial assistance">
          European Union
        </fundAg>
        <fundAg role="Financial assistance">
          UN Women
        </fundAg>
        <fundAg abbr="UNDP" role="Financial assistance">
          United Nations Development Fund
        </fundAg>
      </prodStmt>
      <distStmt>
        <contact affiliation="National Institute of Statistics of Rwanda" URI="www.statistics.gov.rw" email="info@statistics .gov.rw">
          Public Relation and Communication Officer
        </contact>
      </distStmt>
      <serStmt>
        <serName>
          Other Household Survey [hh/oth]
        </serName>
        <serInfo>
          <![CDATA[This is the household survey conducted after the  Fourth Population and  Housing  Census  conducted in Rwanda in 2012]]>
        </serInfo>
      </serStmt>
      <verStmt>
        <version date="2013-04">
          v1: Edited anonymous dataset for public distribution
        </version>
      </verStmt>
    </citation>
    <stdyInfo>
      <subject>
        <keyword vocab="Household" vocabURI="Survey">
          Post Enumeration Survey
        </keyword>
        <keyword vocab="Population " vocabURI="Housing">
          Rwanda
        </keyword>
      </subject>
      <abstract>
        <![CDATA[It has been a long tradition in Rwanda to conduct a Post Enumeration Survey (PES) following the Population and Housing Census. The first of such surveys was conducted following 1991 Census,  the methodology of which has been documented and widely disseminated internationally as an example of a successful PES in developing countries. The Second PES was conducted following the 2002 Population and Housing Census. 

The general objective of this Post Enumeration Survey (PES) was to evaluate coverage and content errors of the 2012 Population and Housing Census data, while  specific objectives are the following:
·Measuring census coverage classified by individual sex, age and residence type (urban and rural); 
·Measuring the contents errors pertinent to a number of selected important census variables, namely sex; age; the ability to read and write in different languages; marital status and the type of sanitation facilities available to the households.]]>
      </abstract>
      <sumDscr>
        <collDate date="2012-09-16" event="start"/>
        <collDate date="2012-09-30" event="end"/>
        <nation abbr="rwa">
          Rwanda
        </nation>
        <geogCover>
          National coverage
        </geogCover>
        <anlyUnit>
          The unit of RPES analysis was member of private household.
        </anlyUnit>
        <universe>
          <![CDATA[The study covered all sampled private  households.]]>
        </universe>
        <dataKind>
          Sample survey data [ssd]
        </dataKind>
      </sumDscr>
      <notes>
        The themes of thsis study include: Characteristics of household members ( sex, ages), their relationship, residence status, literacy, marital status, moving status, and type of toilet facility.
      </notes>
    </stdyInfo>
    <method>
      <dataColl>
        <dataCollector abbr="NISR" affiliation="Ministry of Finance and Economic Planning">
          National Institute of Statistics of Rwanda
        </dataCollector>
        <sampProc>
          <![CDATA[
Conceptually, the PES involves two samples, named the "population" P sample and the "Enumeration" E sample. The P sample consists of the PES sample of segments (Enumeration Areas, EA's) drawn from the same target population, but independently from the census, for the purpose of estimating census omissions when compared to Census records. The E sample is drawn from the cases already enumerated in the Census, but selected for independent re-enumeration for the purpose of estimating census erroneous inclusions when compared to the original Census records. Although the E sample may be separate from the p sample, in practice it is made to overlap completely with the P sample to reduce costs and improve the precision of the estimates. The E sample then consists of the same EA's selected for the PES. A two-way match is conducted between the P sample and the E sample to identify both the omissions and erroneous inclusions. The matching also produces estimate of matched population required in the dual-system estimator of the true population.

The Enumeration Areas, as defined in the mapping operation implemented prior to the 2012 Census, is the Primary Sampling Unit (PSU), while the private household is the Ultimate Sampling Unit (USU). As all Six households included in the sample EA's are included in the sample with certainty, the selection probability of a household is exactly equivalent to the selection probability of the corresponding EA. The EA's list created during the mapping stage constitutes the frame of the EA's. Beside the geographic specification the frame includes estimates of the number of households and the number of the population in each EA. The total number of EA's in Rwanda is 16716 with an average size of 128.6 households each. The size dispersion of EA's is nearly moderate, the standard deviation is about 35.2 households and the coefficient of variation is 27.3 percent. About 80.1 percent of EA's are between 90 and 180 households, while only 1.9 percent of EA's are as small as 60 households or less, there exists about 1 percent of EA's sized 210 or more households.
The normal choice of stratifying variable is the type of residence place (urban, semi-urban, and rural), previous PES surveys in Rwanda (1991 and 2002) exhibit disparity of net coverage error rate between urban and rural. In addition to such explicit stratification of the sampling frame, an implicit stratification based on geographic proximity is also introduced during the sampling selection operation.
The literature review of previous Post Enumeration Surveys carried out in Rwanda (1991, 2002) has revealed that the adopted sample size was 120 EA's for both indicated surveys. As such it was deemed appropriate and logical to maintain this size of the sample for the present PES. Nonetheless, the sample size was independently calculated based on anticipated coverage rate of 97%, deff =2, confidence coefficient of 95%, relative error margin within 10%, and average size of EA of about 128.6 households and about 600 persons and the number of strata is 3, the resulting sample is about 124 EA's which is only 4 EA's greater than the adopted sample size for the present PES. In case of higher coverage rate the relative error margin would be slightly greater than the assumed level of 10%. 
The sample was allocated over the strata in such a  way that:  Urban sample is 40 EA's and Semi-urban sample is 35 EA's.]]>
        </sampProc>
        <deviat>
          The standard deviation is about 35.2 households.
        </deviat>
        <collMode>
          Face-to-face [f2f]
        </collMode>
        <resInstru>
          <![CDATA[The PES questionnaire has been designed in conformity to procedure C of coverage analysis (see the final report P3). It is also consistent with the Dejure enumeration basis of the 2012 Population and Housing Census. It includes information needed to estimate non-movers, in-movers, out-movers, correct enumeration and erroneous enumeration. Provisions are made to record the result of matching operation. 
Concerning content analysis, the questionnaire comprises several census data items that are compared with collected Census data in order to measure the extent of variability between PES responses and the corresponding census responses. These data items include sex, age, marital status and the ability to read and write in any or more of several languages. At the household level, information on the type of bathing facility has also been collected. It is worth noting that the definitions and categories of selected census variables used in the PES are identical to that applied in the Census. In addition to the cover page containing identification data, the questionnaire is organized into four sections: the first deals with non-movers and inmovers, while the second is devoted to out-movers, the third handles information on correct/erroneous enumeration. The last section is designated to the type of bathing facility available to the household. The questionnaire has been designed to be compatible with the recommendation of the UN Statistical Division: Post Enumeration Surveys, Operational guidelines- April 2010.]]>
        </resInstru>
        <sources/>
        <collSitu>
          The field work started with listing operation where two lists were completed: a list of EA boundaries and roads and list of housing units and households, the later list was considered a basis for monitoring the fieldwork on a daily basis. The listing operation was finalized in the first three days, while the entire fieldwork period extended to slightly more than two weeks. The PES reference date is the night of 22/23 of September 2012. Quality checks of completed questionnaires have been performed on a continuous basis and by different levels of field personnel including field editor, team leader and zonal supervisor. On the basis of the household list, the response rate of listed households exceeds 99 percent at the national level.
        </collSitu>
        <actMin>
          <![CDATA[For the purpose of ensuring close supervision of the field work, the country has been divided into five zones, each coincide with the whole province, a big segment of one province or several segments of neighboring provinces. The Country has been segmented into above zones depending on the sample size and its spread inside the zone. The field work started with listing operation where two lists were completed: a list of EA boundaries and roads and list of housing units and households, the later list was considered a basis for monitoring the fieldwork on a daily basis. The listing operation was finalized in the first three days, while the entire fieldwork period extended to slightly more than two weeks. 
 Quality checks of completed questionnaires have been performed on a continuous basis and by different levels of field personnel including field editor, team leader and zonal supervisor.]]>
        </actMin>
        <weight>
          <![CDATA[To obtain unbiased estimates from the PES data it has been necessary to apply appropriate weights to the sample data based on the probabilities of selection. It was also important to calculate measures of sampling variability for Census coverage and content estimates. 
In order to avoid producing biased sample estimates, it was necessary to multiply the data by a sampling weight, or expansion factor. The basic weight for each sample household member was equal to the inverse of his/her probability of selection. As indicated before, since all households and household members were included in the PES Sample with certainty, the selection probability of a certain EA was exactly equivalent to the selection probability of a certain household and a household member within this EA.]]>
        </weight>
        <cleanOps>
          Based on the questionnaire design a CSPRO Computer Program has been designed to capture the RPES data. Data entry was carried out in two computers where questionnaires for different provinces were entered subsequently. Data entry were performed in parallel with the matching operation where the questionnaires for which the matching status of all household members has been judged as “Matched” were entered before starting the reconciliation visits , otherwise data entry was performed after contacting the household through phone calls and/or reconciliation visits to settle down the suspicious cases.Upon the completion of data entry for each province, a SPSS file was created for the purpose of result extraction. However, an intensive data editing was carried out on the SPSS file prior to result extraction. Range as well as consistency checks were carefully performed with special consideration given to the residence status at the time of the Census as well as matching status variables. The province-specific clean data files were concatenated so as to produce a single data file for the whole country, on which basis the results of census coverage and content errors have been generated.
        </cleanOps>
      </dataColl>
      <anlyInfo>
        <respRate>
          The response rate of listed households exceeds 99 percent at the national level.
        </respRate>
        <EstSmpErr>
          <![CDATA[The standard error, or square root of the variance, is used to measure the sampling error. The variance estimator should take into account the different aspects of the sample design, such as the stratification and clustering. Avoiding the time and effort requires  developing custom variance program, and  using an available software package to tabulate the sampling errors. One such software package available for calculating the sampling errors for survey data from stratified cluster sample design such as the present survey is Complex Sample module of SPSS, which is menu-driven and user-friendly. It was  used to calculate sampling errors of totals, means, proportions, and other ratios. It produced subpopulation estimates for each category of a classification variable, and these variables were crossclassified. For each estimate, Complex Sample calculates the standard error, coefficient of variation (CV), a 95 percent confidence interval and the design effect (deff). This software package uses an ultimate cluster variance estimator.]]>
        </EstSmpErr>
      </anlyInfo>
    </method>
    <dataAccs>
      <useStmt>
        <confDec required="yes">
          By accepting the terms of conditions of microdata access, the user agrees to respect the confidentiality.
        </confDec>
        <contact affiliation="Ministry of Finance and Economic Planning" email="info@statistics.gov.rw">
          National Institute of Statistics of Rwanda
        </contact>
        <citReq>
          National Institute of Statistics of Rwanda.Rwanda Post Enumeration Survey-2012[dataset].Version 1. Kigali:NISR, 2014.
        </citReq>
        <conditions>
          This is a licenced file (accessible upon approval)
        </conditions>
        <disclaimer>
          The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
        </disclaimer>
      </useStmt>
    </dataAccs>
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  <dataDscr/>
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