Precision-Based Approach to Number of Replications for Monte Carlo Studies of Robustness and Power

• In Event: Advances in Statistical Methodology

Abstract

Monte Carlo (MC) researchers must determine how many replications, or repeated samples, to draw for each condition under investigation. MC experiments performed with too few replications may produce erroneous results, but too many replications may be inefficient. More replications result in more power and precision, but there are diminishing returns as replications increase. The purpose of this paper is to examine the number of replications needed in MC experiments designed to investigate robustness and statistical power. A precision-based method for determining an appropriate number of replications, uniquely combined here with robustness criteria, is recommended. Using both analytical and MC methods, implications of this method are considered and interpreted.

Authors

• Gordon P. Brooks, Ohio University - Athens

• Emily A. Price, Ohio University

• George A. Johanson, Ohio University