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010   $a981-19-3639-0
035   $a(CKB)5700000000100487
035   $a(MiAaPQ)EBC7028997
035   $a(Au-PeEL)EBL7028997
035   $a(OCoLC)1334995976
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/87693
035   $a(PPN)263902943
035   $a(EXLCZ)995700000000100487
100   $a20220919d2022      fy             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHow data quality affects our understanding of the earnings distribution /$fReza C. Daniels
210   $aSingapore$cSpringer Nature$d2022
210  1$aSingapore :$cSpringer,$d2022.
210  4$d©2022.
215   $a1 online resource (xx, 114 pages) $cillustrations (some color)
311 1 $a981-19-3638-2 
327   $aIntroduction A Framework for Investigating Micro Data Quality, with Application to South African Labour Market Household Surveys Questionnaire Design and Response Propensities for Labour Income Micro Data Univariate Multiple Imputation for Coarse Employee Income Data Conclusion: How Data Quality A?ects our Understanding of the Earnings Distribution
330   $aThis open access book demonstrates how data quality issues affect all surveys and proposes methods that can be utilised to deal with the observable components of survey error in a statistically sound manner. This book begins by profiling the post-Apartheid period in South Africa's history when the sampling frame and survey methodology for household surveys was undergoing periodic changes due to the changing geopolitical landscape in the country. This book profiles how different components of error had disproportionate magnitudes in different survey years, including coverage error, sampling error, nonresponse error, measurement error, processing error and adjustment error.
606   $aIncome distribution$xStatistical methods
606   $aMathematical statistics
606   $aDistribució de la renda$2thub
606   $aEstadística matemàtica$2thub
608   $aLlibres electrònics$2thub
610   $aMethodology for Collecting
610   $aEstimating and Organizing Microeconomic Data
610   $aSurvey Methods
610   $aTotal Survey Error
610   $aResponse Propensity Models
610   $aMultiple Imputation
610   $aIncome Distribution
615  0$aIncome distribution$xStatistical methods.
615  0$aMathematical statistics.
615  7$aDistribució de la renda
615  7$aEstadística matemàtica
700   $aDaniels$b Reza Che$01255142
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a996483153703316
996   $aHow data quality affects our understanding of the earnings distribution$92910256
997   $aUNISA