Assessing Fit in Common Factor Models Using Empirical Moment Functions.

This article discusses the limitations of current goodness-of-fit diagnostics in common factor models and proposes a novel fit assessment framework. The framework is inspired by item response theory models and uses empirical moment functions to estimate conditional moments for response variables. Residuals are then calculated as discrepancies between empirical and model-implied moment functions. The article presents two types of formal statistical tests based on these residuals and evaluates their performance through a simulation study. The results suggest that the proposed tests have well-controlled Type I error rates and decent power. The authors also discuss the potential use of empirical moment functions to detect other sources of misfit in future research. [Extracted from the article]

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