DEVELOPMENT OF A NEW OUTLIER STATISTIC FOR METAANALYTIC DATA
成果类型：
Article
署名作者：
HUFFCUTT, AI; ARTHUR, W
署名单位：
Texas A&M University System; Texas A&M University College Station
刊物名称：
JOURNAL OF APPLIED PSYCHOLOGY
ISSN/ISSBN：
0021-9010
DOI：
10.1037/0021-9010.80.2.327
发表日期：
1995
页码：
327-334
关键词：
摘要：
This article describes the development of a new technique for identifying outlier coefficients in meta-analytic data sets. Denoted as the sample-adjusted meta-analytic deviancy statistic or SAMD, this technique takes into account the sample size on which each study is based when determining outlier status. An empirical test of the SAMD statistic with an actual meta-analytic data set resulted in a substantial reduction in residual variabilities and a corresponding increase in the percentage of variance accounted for by statistical artifacts after removal of outlier study coefficients. Moreover, removal of these coefficients helped to clarify what was a confusing and difficult-to-explain finding in this meta-analysis. It is suggested that analysis for outliers become a routine part of meta-analysis methodology. Limitations and directions for future research are discussed.
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