DEVELOPMENT OF A NEW OUTLIER STATISTIC FOR METAANALYTIC DATA

This article describes the development of a new technique for identify ing outlier coefficients in meta-analytic data sets. Denoted as the sa mple-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 wi th an actual meta-analytic data set resulted in a substantial reductio n in residual variabilities and a corresponding increase in the percen tage 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 findi ng in this meta-analysis. It is suggested that analysis for outliers b ecome a routine part of meta-analysis methodology. Limitations and dir ections for future research are discussed.