2025-06-25 –, Second floor 214
Confirmatory factor analysis (CFA) is one of the most central analytic techniques in social sciences. However, model fit assessment still heavily relies on arbitrary cutoffs (e.g., RMSEA ≤ .05, CFI ≥ .95), which lack universal validity. Misinterpreting these thresholds contributes to the accumulation of misspecified models in the literature. In our talk, we introduce an up-to-date CFA fit assessment framework based on conceptual understanding, local fit evaluation, and dynamic benchmarks. Our tutorial comes with all the resources needed to bring CFA-fitting into the new century: an R script, empirical examples, and a decision tree. By abandoning inflexible cutoffs and embracing a more nuanced model fit evaluation, we can shrink the number of misspecified models in the literature and, consequently, refine our theories.
