_:n33a0a6129de94c70b3b86f8aca7fe5dexb0
<http://schema.org/description>
"Abstract\r\n---------------------------\r\n\r\nThe GHS is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, employment, health, housing and household access to services.\r\n\r\nGeographic coverage\r\n---------------------------\r\n\r\nThe survey is representative at national level and at provincial level.\r\n\r\nAnalysis unit\r\n---------------------------\r\n\r\nHouseholds and individuals\r\n\r\nUniverse\r\n---------------------------\r\n\r\nThe survey covered all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as students' hostels, old age homes, hospitals, prisons and military barracks.\r\n\r\nKind of data\r\n---------------------------\r\n\r\nSample survey data\r\n\r\nSampling procedure\r\n---------------------------\r\n\r\nThe sample is multi-stage stratified using probability proportional to size principles. The first stage is stratification by province, then by type of area within each province. Primary sampling units (PSUs) are then selected proportionally within each stratum (urban or non-urban) in all provinces.\r\n\r\nMode of data collection\r\n---------------------------\r\n\r\nFace-to-face [f2f]\r\n\r\nResearch instrument\r\n---------------------------\r\n\r\nGHS uses questionnaires as data collection instruments\r\n\r\nData appraisal\r\n---------------------------\r\n\r\nEarlier versions of the GHS datasets 2002 to 2007 include a District Council variable. This is no longer available in the later versions issued by Statistics SA. They caution that although the GHS 2005-2007 sample was designed to report at DC level, estimations are not reliable at this level. The 2008 - 2013 sample was designed to report at provincial and metro level. However, StatsSA did not take the absent population at metro into account when weighting the data and therefore this data is not reliable at Metro level. \n\nThe new programs that were introduced for weighting of the general household surveys from 2008 onwards, discard all records with missing values for age, sex or population group (for observations at household level, they are the values for age, sex or population group of the household head). This means that missing values of those variables were imputed. The emphasis was on obtaining reliable imputations rather than a 100% imputation rate, so some persons/households were discarded during the weighting."
<https://datafirst.uct.ac.za/dataportal/index.php/catalog/90>