The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index.
Principles and practice in reporting structural equation analyses.
Abstract
Principles for reporting analyses using structural equation modeling are reviewed, with the goal of supplying readers with complete and accurate information. It is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability. Nonnormality and missing data problems should also be addressed. A complete set of parameters and their standard errors is desirable, and it will often be convenient to supply the correlation matrix and discrepancies, as well as goodness-of-fit indices, so that readers can exercise independent critical judgment. A survey of fairly representative studies compares recent practice with the principles of reporting recommended here.
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“The final valid questionnaires of this study were 219 cases, which satisfied the minimum requirement of the sample size of 200 people for structural equation modelling (McDonald and Ho 2002).”
From The Relationship Between Knowledge, Psychological Flexibility, Anxiety and Healthy Behaviour in Stroke Patients: A Chain Mediation Model. (2026) · cites this paper as McDonald and Ho 2002
In the citing paper
“Good model fit is indicated by χ ²/df below three, CFI and NNFI values greater than .90, and RMSEA and SRMR below .08 (Hu and Bentler 1999; McDonald and Ho 2002).”
From Awareness Versus Un-Clinging: Which Matters in Mindfulness? (2017) · cites this paper as McDonald and Ho 2002
Citations
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“Models are usually considered to fit well when the chi-square value is nonsignificant compared to the degrees of freedom; the RMSEA is below .10; and the NFI, TLI, and RNI are above .90 (McDonald & Ho, 2002).”
MethodFabris, M. A., Lin, S., & Longobardi, C. (2023) · Journal of School Psychology · doi:10.1016/j.jsp.2023.101227 · Cited by 46
“…used to evaluate the overall goodness-of-fit included the (a) chi-square statistic, (b) Root Mean Square Error of Approximation (RMSEA ≤ 0.08; McDonald & Ho, 2002), (c) Comparative Fit Index (CFI ≥ 0.90; Bentler, 1992), and (d) Standardized Root Mean Square Residual (SRMR ≤ 0.08; Hu &…”
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Testing Spearman's hypotheses using a bi-factor model with WAIS-IV/WMS-IV standardization data
Frisby, C. L., & Beaujean, A. A. (2015) · Intelligence · doi:10.1016/j.intell.2015.04.007 · Cited by 39
Cockcroft, K., Alloway, T., Copello, E., & Milligan, R. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00297 · Cited by 39
“RMSEA and SRMR values below 0.05 indicate a good fit, values between 0.08 and 0.10 indicate a mediocre fit, and values above 0.10 indicate a poor fit (McDonald and Ho, 2002).”
InfluentialYu, W., Chen, J., Sun, S., Liu, P., Ouyang, L., & Hu, J. (2021) · Psycho-Oncology · doi:10.1002/pon.5667 · Cited by 40
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“Model fit was assessed with the comparative fit index (CFI) and the root mean square error of approximation (RMSEA) given that chi-square is known to be sensitive to sample size (McDonald & Ho, 2002).”
MethodNadlifatin, R., Lin, S.-C., Rachmaniati, Y., Persada, S., & Razif, M. (2016) · Sustainability · doi:10.3390/su8111165 · Cited by 51
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Types of Social Connectedness and Loneliness: the Joint Moderating Effects of Age and Gender
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“RMSEA values of .06 and below and CFI values of .95 and above indicate strong model fit, and CFI C .90 and RMSEA B .08 indicate adequate fit (Browne and Cudeck 1993; McDonald and Ho 2002).”
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“80 were considered an acceptable fit (McDonald and Ho, 2002).”
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Becker, A. B. C., Maurer, J., Daseking, M., & Pauls, F. (2024) · Journal of Intelligence · doi:10.3390/jintelligence12010006 · Cited by 11
“The evaluation of each measurement invariance model was based on a preselected set of model fit indexes in order to overcome the limitations of each single index (see Kline 2016; McDonald and Ho 2002; Thompson 2000, for an overview).”
MethodAwareness Versus Un-Clinging: Which Matters in Mindfulness?
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“Good model fit is indicated by χ²/df below three, CFI and NNFI values greater than .90, and RMSEA and SRMR below .08 (Hu and Bentler 1999; McDonald and Ho 2002).”
MethodChen, H., Zhu, J., Liao, Y.-K., & Keith, T. Z. (2020) · Journal of Psychoeducational Assessment · doi:10.1177/0734282920930542 · Cited by 8
“Multiple indices of model fit were used to evaluate and compare the models (Bentler & Bonett, 1980; Hoyle & Panter, 1995; Hu & Bentler, 1998, 1999; Kline, 2016; Marsh et al., 1988; McDonald & Ho, 2002).”
MethodGong, W., & Xu, C. (2024) · Sage Open · doi:10.1177/21582440241293327 · Cited by 8
“…is close to x 2 / df = 2 (Ullman, 2001), RMSEA = 0.065, although the strict standard is greater than 0.05, it can still be accepted if below 0.8 (McDonald & Ho, 2002), GFI is 0.796, which does not reach the standard of 0.900, but Bollen (1990) proposed that GFI and AGFI will be underestimated…”
InfluentialMa, R., Qiao, M., Zhou, Y., Sun, W., Lv, Y., Zhou, X., Wang, Y., Wu, X., & Yu, R. (2026) · Journal of Clinical Nursing · doi:10.1111/jocn.17820 · Cited by 3
Metadata
- Authors
- McDonald, R. P., & Ho, M.-H. R.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- ORCID
- Ho, Moon-Ho Ringo
- Venue
- Psychological Methods
- Published
- 2002
- Volume
- 7
- Issue
- 1
- Pages
- 64-82
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2134368355
- Cited by
- 4,734
- References
- 102
- Citations by year
- 2026: 176 · 2025: 300 · 2024: 313 · 2023: 336 · 2022: 348 · 2021: 323 · 2020: 327 · 2019: 289 · 2018: 236 · 2017: 236 · 2016: 206 · 2015: 202 · 2014: 198 · 2013: 208 · 2012: 185
- FWCI
- 58.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- structural equation modeling, reporting guidelines, model justification, model identifiability, non-normality, missing data, goodness-of-fit indices, standard errors, correlation matrix, model mismatch, critical appraisal
- MeSH terms
- Humans, Models, Psychological, Research Design, Linear Models
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