Meta-analytic structural equations modeling is increasingly used in theory testing. There has been much debate when meta-analyzed correlation matrices are used in structural equations modeling on whether to use mean observed correlations (i.e., corrected only for sampling error) or correlations corrected for study artifacts such as unreliability in measures. This paper investigates whether the fit indices are affected by the corrections and if the stability of the paths (i.e., changes in significance, magnitude, and relative strengths or rank order) is affected by the corrections. Results suggest that substantive model conclusions are generally unaffected by study artifacts and related statistical corrections as long as the variables included in the path analyses had typical levels of reliability as found in the psychological literature. More specifically, all models examined exhibited similar model fit and pathway stability. Copyright © 2011 John Wiley & Sons, Ltd.