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Wiley InterScience | |||||||||||||
  Journal of Marriage and FamilyVolume 67 Issue 4, Pages 1012 - 1028 Published Online: 20 Sep 2005 Copyright © National Council on Family Relations, 2010 Published on behalf of the National Council on Family Relations
Abstract | References | Full Text: HTML, PDF (Size: 148K) | Related Articles | Citation Tracking  Working With Missing Values Copyright National Council on Family Relations, 2005 KEYWORDS
MAR
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MCAR
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missing data
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missing values
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multiple imputation
ABSTRACTLess than optimum strategies for missing values can produce biased estimates, distorted statistical power, and invalid conclusions. After reviewing traditional approaches (listwise, pairwise, and mean substitution), selected alternatives are covered including single imputation, multiple imputation, and full information maximum likelihood estimation. The effects of missing values are illustrated for a linear model, and a series of recommendations is provided. When missing values cannot be avoided, multiple imputation and full information methods offer substantial improvements over traditional approaches. Selected results using SPSS, NORM, Stata (mvis/micombine), and Mplus are included as is a table of available software and an appendix with examples of programs for Stata and Mplus. Received: 08 July 2005; Accepted: 09 September 2005; | 
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