title: Monte Carlo based statistical power analysis for mediation models: methods and software.
abstract: The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.
authors: University of Notre Dame, Notre Dame, USA, ZhiyongZhang@nd.edu.
authors: Zhiyong
authors: Z
authors: Zhang
mesh_terms: D000328:Adult; D000465:Algorithms; D035841:Behavioral Research / Q000379:methods*; D002648:Child; D003196:Computer Graphics; D016001:Confidence Intervals; D003626:Data Display; D003627:Data Interpretation, Statistical; D004521:Educational Measurement; D004522:Educational Status; D005260:Female; D006801:Humans; D008960:Models, Psychological; D009010:Monte Carlo Method; D009034:Mother-Child Relations / Q000523:psychology; D017008:Negotiating / Q000523:psychology; D012016:Reference Values; D018401:Sample Size; D012931:Social Environment; D012984:Software; D012985:Software Design