Meta-Analysis and Estimating Many Quantities

Part of the Springer Texts in Statistics book series (STS)

Meta-analysis is a term used for summarising a collection of studies that have the same or closely related targets. Each study may contain only modest information about the target, and meta-analysis seeks to synthesise this information and conclude with a single inferential statement. The main challenges in meta-analysis are related to the incompleteness of the studies: some are not reported at all, others are reported in a format that does not contain the items required for the meta-analysis, and, arguably, some studies that should have been were not conducted. Each study has its own context, such as the country or region in which it is conducted, time period (year), recruitment process, measurement and data-recording procedures, and other details of the design and protocol, which exert an influence on the targets of the studies and make the meta-analysis more complex.


Sampling Variance Unbiased Estimator Alternative Estimator Shrinkage Estimator Average Context 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer 2008

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