Cheat sheet · printable

Reliability and validity thresholds

Q: What is a good Cronbach’s alpha?

Values of .70 or higher are generally acceptable, .80 or higher good, and above .95 may indicate redundant items. In exploratory research, .60 to .70 can be acceptable.

Q: What is the AVE threshold?

Average variance extracted should be at least .50, meaning the construct explains at least half of the variance of its indicators (Fornell & Larcker, 1981).

Q: What is the HTMT cut-off?

HTMT values below .85 (conceptually distinct constructs) or .90 (conceptually similar constructs) indicate discriminant validity (Henseler et al., 2015).

Q: Which fit indices should I report for CFA?

Report χ² with df and p, CFI, TLI, RMSEA with its 90% confidence interval and SRMR. Common cut-offs are CFI and TLI ≥ .95, RMSEA ≤ .06 and SRMR ≤ .08 (Hu & Bentler, 1999).

Every common cut-off for measurement quality and model fit on one page, each with the source to cite in your thesis or paper. Click a measure to calculate it for your data.

Updated 17 October 2026 · By Bibin Xavier

Reliability

Measure	Threshold	Source
Cronbach’s alpha (α)	≥ .70 acceptable; .60–.70 acceptable in exploratory research; > .95 may signal redundant items	Nunnally & Bernstein (1994); Hair et al. (2019)
McDonald’s omega (ω)	≥ .70	Hayes & Coutts (2020)
Composite reliability (ρc)	.70–.95 (.60–.70 in exploratory research); > .95 problematic	Hair et al. (2019)
Reliability coefficient ρA	≥ .70; usually lies between α and ρc	Dijkstra & Henseler (2015)
Split-half (Spearman–Brown)	≥ .70	Nunnally & Bernstein (1994)
Indicator reliability (outer loading)	≥ .708; .40–.70 delete only if CR or AVE improves; < .40 delete	Hair et al. (2019, 2022)

Convergent and discriminant validity

Measure	Threshold	Source
Average variance extracted (AVE)	≥ .50	Fornell & Larcker (1981)
Fornell–Larcker criterion	√AVE of each construct larger than its correlations with every other construct	Fornell & Larcker (1981)
HTMT ratio	< .85 for conceptually distinct constructs; < .90 for similar constructs; bootstrap CI should not include 1	Henseler, Ringle & Sarstedt (2015)
Cross-loadings	Each item loads highest on its own construct	Hair et al. (2022)

Collinearity and common method bias

Measure	Threshold	Source
VIF (PLS-SEM predictors)	< 3 ideal; 3–5 possible problem; ≥ 5 critical	Hair et al. (2019)
Full collinearity VIF	≤ 3.3 suggests no common method bias	Kock (2015)
Harman’s single factor test	First unrotated factor explains < 50% of variance	Podsakoff et al. (2003)

Model fit (CB-SEM and CFA)

Measure	Threshold	Source
CFI and TLI	≥ .95 good; ≥ .90 acceptable	Hu & Bentler (1999)
RMSEA	≤ .06 good; ≤ .08 reasonable; > .10 poor	Hu & Bentler (1999); Browne & Cudeck (1993)
SRMR	≤ .08	Hu & Bentler (1999)
χ²/df	< 3 is a common rule of thumb; not recommended as the only criterion	Kline (2016)

Structural model (PLS-SEM)

Measure	Threshold	Source
R²	.75 substantial, .50 moderate, .25 weak (varies by discipline)	Hair, Ringle & Sarstedt (2011)
Effect size f²	.02 small, .15 medium, .35 large	Cohen (1988)
Q² (blindfolding)	> 0 indicates predictive relevance	Hair et al. (2019)
PLSpredict Q²predict	> 0; compare RMSE or MAE with the linear model benchmark	Shmueli et al. (2019)
SRMR (PLS-SEM)	< .08 (approximate fit)	Henseler, Hubona & Ray (2016)

Factor analysis (EFA)

Measure	Threshold	Source
KMO measure of sampling adequacy	≥ .90 marvelous, ≥ .80 meritorious, ≥ .70 middling, ≥ .60 mediocre, ≥ .50 miserable, < .50 unacceptable	Kaiser (1974)
Bartlett’s test of sphericity	p < .05	Bartlett (1954)
Factor loadings	≥ .40 commonly used; cross-loadings should differ by ≥ .20	Common rule of thumb (see Hair et al., 2019)

Agreement and content validity

Measure	Threshold	Source
Intraclass correlation (ICC)	< .50 poor, .50–.75 moderate, .75–.90 good, > .90 excellent	Koo & Li (2016)
Cohen’s and Fleiss’ kappa	.00–.20 slight, .21–.40 fair, .41–.60 moderate, .61–.80 substantial, .81–1.00 almost perfect	Landis & Koch (1977)
Content validity index	I-CVI ≥ .78 (6 or more experts); S-CVI/Ave ≥ .90	Polit & Beck (2006)

Normality for SEM

Measure	Threshold	Source
Skewness and kurtosis	\|skewness\| < 2 and \|kurtosis\| < 7	West, Finch & Curran (1995)

Thresholds are guidelines, not laws: report the values, justify borderline decisions and follow the conventions of your field.

Bartlett, M. S. (1954). A note on the multiplying factors for various χ² approximations. Journal of the Royal Statistical Society: Series B, 16(2), 296–298.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Sage.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Erlbaum.
Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.
Hayes, A. F., & Coutts, J. J. (2020). Use omega rather than Cronbach’s alpha for estimating reliability. But…. Communication Methods and Measures, 14(1), 1–24.
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis. Structural Equation Modeling, 6(1), 1–55.
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36.
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10.
Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research. Journal of Applied Psychology, 88(5), 879–903.
Polit, D. F., & Beck, C. T. (2006). The content validity index: Are you sure you know what’s being reported? Research in Nursing & Health, 29(5), 489–497.
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347.
West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with nonnormal variables. In R. H. Hoyle (Ed.), Structural equation modeling (pp. 56–75). Sage.

Frequently asked questions

What is a good Cronbach’s alpha?

Values of .70 or higher are generally acceptable, .80 or higher good, and above .95 may indicate redundant items. In exploratory research, .60 to .70 can be acceptable.

What is the AVE threshold?

Average variance extracted should be at least .50, meaning the construct explains at least half of the variance of its indicators (Fornell & Larcker, 1981).

What is the HTMT cut-off?

HTMT values below .85 (conceptually distinct constructs) or .90 (conceptually similar constructs) indicate discriminant validity (Henseler et al., 2015).

Which fit indices should I report for CFA?

Report χ² with df and p, CFI, TLI, RMSEA with its 90% confidence interval and SRMR. Common cut-offs are CFI and TLI ≥ .95, RMSEA ≤ .06 and SRMR ≤ .08 (Hu & Bentler, 1999).

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How to cite this page

Using these values in a thesis, paper or class handout? Please cite the page so others can find it. It keeps the site free.

APA 7

Xavier, B. (2026). Reliability and validity thresholds cheat sheet [Web page]. FreeStatisticalTools.com. https://freestatisticaltools.com/reliability-validity-thresholds/

BibTeX

@misc{xavier_reliabilityvaliditythresholds_2026,
  author = {Xavier, Bibin},
  title = {Reliability and validity thresholds cheat sheet},
  publisher = {FreeStatisticalTools.com},
  year = {2026},
  url = {https://freestatisticaltools.com/reliability-validity-thresholds/}
}