Journal article

Imputing cross-sectional missing data: comparison of common techniques

G Hawthorne, P Elliott

Australian and New Zealand Journal of Psychiatry | SAGE PUBLICATIONS LTD | Published : 2005

Abstract

OBJECTIVE: Increasing awareness of how missing data affects the analysis of clinical and public health interventions has led to increasing numbers of missing data procedures. There is little advice regarding which procedures should be selected under different circumstances. This paper compares six popular procedures: listwise deletion, item mean substitution, person mean substitution at two levels, regression imputation and hot deck imputation. METHOD: Using a complete dataset, each was examined under a variety of sample sizes and differing levels of missing data. The criteria were the true t-values for the entire sample. RESULTS: The results suggest important differences. If missing data ar..

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University of Melbourne Researchers