Power calculation in multiply imputed data

Multiple imputation (MI) has been proven an effective procedure to deal with incomplete datasets. Compared with complete case analysis (CCA), MI is more efficient since it uses the information provided by incomplete cases which are simply discarded in CCA. A few simulation studies have shown that st...

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Bibliographic Details
Published inStatistical papers (Berlin, Germany) Vol. 62; no. 1; pp. 533 - 559
Main Authors Zha, Ruochen, Harel, Ofer
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2021
Springer Nature B.V
Subjects
Data analysis
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Finance
Insurance
Management
Mathematical analysis
Mathematics and Statistics
Operations Research/Decision Theory
Probability Theory and Stochastic Processes
Regular Article
Simulation
Statistics
Statistics for Business
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Summary:Multiple imputation (MI) has been proven an effective procedure to deal with incomplete datasets. Compared with complete case analysis (CCA), MI is more efficient since it uses the information provided by incomplete cases which are simply discarded in CCA. A few simulation studies have shown that statistical power can be improved when MI is used. However, there is a lack of knowledge about how much power can be gained. In this article, we build a general formula to calculate the statistical power when MI is used. Specific formulas are given for several different conditions. We demonstrate our finding through simulation studies and a data example.
ISSN:0932-5026
1613-9798
DOI:10.1007/s00362-019-01098-8