In research concerning model invariance across populations, researchers have discussed the limitations of the conventional 2 difference test (2 test). There have been some research efforts in using goodness-of-fit indexes (i.e., goodness-of-fit indexes) for assessing multisample model invariance, and some specific recommendations have been made (Cheung Rensvold, 2002). Because goodness-of-fit indexes were designed to assess model fit in terms of covariance structure, it is not clear how they will perform when mean structure invariance is the research focus. This study extends the previous work (Cheung Rensvold, 2002), and evaluates how goodness-of-fit indexes perform in mean structure invariance analysis. By using a Monte Carlo simulation experiment, the performance of goodness-of-fit indexes in detecting population mean structure difference is evaluated. The findings suggest that, in general, goodness-of-fit indexes are so sensitive to model size that they are not generally useful in mean structure invariance analysis
