This article challenges the wide-spread practice of using Hu and Bentler's (1999) cut-off values (CFI > .95, TLI > .95, RMSEA < .06, SRMR < .08) as the sole indicator of good test fit. Two underlying assumptions are questioned: (1) that these criteria apply universally and (2) that very high CFI/TLI and low RMSEA/SRMR represent optimal fit. An exclusive focus on Hu and Bentler's criteria favors top-down test construction with narrow, pre-defined scales, potentially neglecting bottom-up approaches that identify items reflecting real-world complexities. This article proposes an alternative approach: compiling practice-based distributions of fit indices from existing tests. An analysis of 161 datasets revealed distinct high-probability regions for TLI, RMSEA, and SRMR, largely outside the Hu and Bentler thresholds and dependent on the statistical technique used for analysis. Based on the distributions, indicators are developed to differentiate between unifactorial, multifactorial, and hierarchical scales. The indicators are intended to complement, not replace, statistical model comparison by providing a practice-oriented perspective.
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Marc Brysbaert (2024) studied this question.
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