Comparing meta-analytic moderator estimation techniques under realistic conditions
成果类型：
Article
署名作者：
Steel, PD; Kammeyer-Mueller, JD
署名单位：
University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
刊物名称：
JOURNAL OF APPLIED PSYCHOLOGY
ISSN/ISSBN：
0021-9010
DOI：
10.1037//0021-9010.87.1.96
发表日期：
2002
页码：
96-111
关键词：
摘要：
One of the most problematic issues in contemporary meta-analysis is the estimation and interpretation or moderating effects. Monte Carlo analyses are developed in this article that compare bivariate correlations, ordinary least squares and weighted least squares (WLS) multiple regression, and hierarchical subgroup (HS) analysis for assessing the influence of continuous moderators under conditions of multicollinearity and skewed distribution of study sample sizes (heteroscedasticity). The results show that only WLS is largely unaffected by multicollinearity and heteroscedasticity, whereas the other techniques are substantially weakened. Of note, HS, one of the most popular methods, typically provides the most inaccurate results, whereas WLS, one of the least popular methods, typically provides the most accurate results.
来源URL：