Tools for analyzing multiple imputed datasets

John B. Carlin, Ning Li, Philip Greenwood and Carolyn Coffey
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John B. Carlin: Murdoch Children's Research Institute and University of Melbourne Department of Paediatrics
Philip Greenwood: Murdoch Children's Research Institute and University of Melbourne Department of Paediatrics
Carolyn Coffey: Murdoch Children's Research Institute and University of Melbourne Department of Paediatrics

Stata Journal, 2003, vol. 3, issue 3, 226-244

Abstract: The method of multiple imputation (MI) is used increasingly for analyzing datasets with missing observations. Two sets of tasks are required in order to implement the method: (a) generating multiple complete datasets in which missing values have been imputed by simulating from an appropriate probability distribution and (b) analyzing the multiple imputed datasets and combining complete data inferences from them to form an overall inference for parameters of interest. An increasing number of software tools are available for task (a), although this is difficult to automate, because the method of imputation should depend on the context and available covariate data. When the quantity of missing data is not great, the sensitivity of results to the imputation model may be relatively low. In this context, software tools that enable task (b) to be performed with similar ease to the analysis of a single dataset should facilitate the wider use of multiple imputation. Such tools need not only to implement techniques for inference from multiple imputed datasets but also to allow standard manipulations such as transformation and recoding of variables. In this article, we describe a set of Stata commands that we have developed for manipulating and analyzing multiple datasets. Copyright 2003 by StataCorp LP.

Keywords: missing data; multiple imputation; RubinÕs rule of combination; overall estimates (search for similar items in EconPapers)
Date: 2003
References: View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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