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  Vol. 65 No. 2, February 2008 TABLE OF CONTENTS
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The Missing Data Problem in Meta-analyses

Winfried Rief, PhD; Stefan G. Hofmann, PhD

Since this article does not have an abstract, we have provided the first 150 words of the full text and any section headings.

The article by Leichsenring and colleagues1 presented an interesting meta-analysis of 17 studies to examine the efficacy of short-term psychodynamic psychotherapy. As in many other meta-analyses, they do not report any analyses of the treatment dropout rates and attrition rates during the follow-up phase of the studies. However, every meta-analysis can be only as good as the studies it is based on. Factors that influence effect size estimations include study design issues and sample characteristics.2 Missing data are particularly problematic because they impose a serious threat to the internal and external validity of a clinical trial.

A number of strategies have been developed to handle the missing data problem, including least squares analyses, imputation methods, and likelihood-based approaches.3 However, even the best estimator cannot replace the actual datum, and a study with few missing data provides more valuable results than a similarly well-designed . . . [Full Text of this Article]


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RELATED ARTICLE

The Efficacy of Short-term Psychodynamic Psychotherapy in Specific Psychiatric Disorders: A Meta-analysis
Falk Leichsenring, Sven Rabung, and Eric Leibing
Arch Gen Psychiatry. 2004;61(12):1208-1216.
ABSTRACT | FULL TEXT  






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