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Reducing the Time and Effort Required by Meta-Analysis through the Use of Random Sampling

Meta-analysis has become a foundation of scientific inquiry. It is used to statistically integrate the findings of many studies to come to generalizable conclusions. Unfortunately, in some cases, the number of studies available for the analysis can make the meta-analysis process extremely difficult and lengthy. The current study attempted to alleviate this problem by investigating the effects of random sampling of the studies used in the analysis in recently published meta-analyses to determine if a subsample of studies could produce accurate results. In the process, the characteristics of recent meta-analyses were investigated, as well as the percentage of randomly sampled studies that is needed to produce accurate moderator findings. Results of this investigation provide preliminary support for the use of random sampling in medium and large-scale meta-analyses, or analyses in which a medium (35 or more) to large number (91 or more) of studies fit the analystâs inclusion criteria. Random sampling was able to reproduce the main effect sizes found in these types of meta-analyses. The use of random sampling to replicate the results of meta-analyses involving moderators, however, was only successful in large scale analyses. It is hoped that these results will encourage the use of random sampling in future meta-analyses by providing guidelines for its use, as this procedure can drastically reduce the amount of work required.

Identiferoai:union.ndltd.org:NCSU/oai:NCSU:etd-03182008-184923
Date21 April 2008
CreatorsDuVernet, Amy
ContributorsDr. Mark A Wilson, Dr. Joan J. Michael, Dr. S. Bartholomew Craig
PublisherNCSU
Source SetsNorth Carolina State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.lib.ncsu.edu/theses/available/etd-03182008-184923/
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