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2012 | OriginalPaper | Buchkapitel

7. Missing Data in Meta-analysis: Strategies and Approaches

verfasst von : Terri D. Pigott

Erschienen in: Advances in Meta-Analysis

Verlag: Springer US

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Abstract

This chapter provides an overview of missing data issues that can occur in a meta-analysis. Common approaches to missing data in meta-analysis are discussed. The chapter focuses on the problem of missing data in moderators of effect size. The examples demonstrate the use of maximum likelihood methods and multiple imputation, the only two methods that produce unbiased estimates under the assumption that data are missing at random. The methods discussed in this chapter are most useful in testing the sensitivity of results to missing data.

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Metadaten
Titel
Missing Data in Meta-analysis: Strategies and Approaches
verfasst von
Terri D. Pigott
Copyright-Jahr
2012
Verlag
Springer US
DOI
https://doi.org/10.1007/978-1-4614-2278-5_7