Handling Item Nonresponse in the U.S. Component of the IEA Reading Literacy Study

Marianne Winglee, Graham Kalton, Keith Rust and Daniel Kasprzyk

Journal of Educational and Behavioral Statistics, 2001, vol. 26, issue 3, 343-359

Abstract: The U.S. component of the International Reading Literacy Study provides a data set where nonresponses to the background questionnaire items were filled in using imputation methods (mainly hot-deck). This study uses the completed data set for analyses and compares the results with those from other methods of handling missing data. Analyses conducted include regression and hierarchical linear models. The imputed data set yields results similar to those produced by available case analyses (pairwise deletion) and by the estimation and maximization algorithm analyses. The results, however, are different from those produced by complete case analyses (casewise deletion). For most analyses of the Reading Literacy Study, the data set completed by imputation is a convenient option.

Keywords: available case analysis; complete case analysis; EM algorithm; hot-deck imputation; item nonresponse (search for similar items in EconPapers)
Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:26:y:2001:i:3:p:343-359

DOI: 10.3102/10769986026003343

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