Abstract

Abstract The use of Monte Carlo simulations for the empirical assessment of statistical estimators is becoming more common in structural equation modeling research. Yet, there is little guidance for the researcher interested in using the technique. In this article we illustrate both the design and implementation of Monte Carlo simulations. We present 9 steps in planning and performing a Monte Carlo analysis: (1) developing a theoretically derived research question of interest, (2) creating a valid model, (3) designing specific experimental conditions, (4) choosing values of population parameters, (5) choosing an appropriate software package, (6) executing the simulations, (7) file storage, (8) troubleshooting and verification, and (9) summarizing results. Throughout the article, we use as a running example a Monte Carlo simulation that we performed to illustrate many of the relevant points with concrete information and detail.

Keywords

Monte Carlo methodComputer scienceMathematicsStatistics

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Publication Info

Year
2001
Type
article
Volume
8
Issue
2
Pages
287-312
Citations
327
Access
Closed

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Pamela Paxton, Patrick J. Curran, Kenneth A. Bollen et al. (2001). Monte Carlo Experiments: Design and Implementation. Structural Equation Modeling A Multidisciplinary Journal , 8 (2) , 287-312. https://doi.org/10.1207/s15328007sem0802_7

Identifiers

DOI
10.1207/s15328007sem0802_7