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Principles and practice in reporting structural equation analyses.

McDonald, Roderick P., Ho, Moon-Ho Ringo·2002·Psychological Methods

DOI 10.1037/1082-989x.7.1.64

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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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“However, because virtually any factor model could be rejected if the sample size is large enough, many authors recommended more ‘‘practical’’ indices of fit (e.g., Bentler 1990; Fabrigar et al. 1999; McDonald and Ho 2002; Schweizer 2010).”
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“Prior work by McDonald and Ho (2002) suggests that two of these indices, the Comparative-Fit-Index (CFI) and Root Mean Square Error of Approximation (RMSEA), along with the chi-square statistic, when considered together, will constitute appropriate measures for examining the fit of the theoretical model tested.”
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“Residual variances of the parceled indicators are included in the bottom left portion of the matrix in Table 2 (McDonald & Ho, 2002.1 Results of the overall model analysis suggested a reasonable overall model fit for the proposed model of watershed protection shown in Fig.”
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“These indices indicate how well a model fits the sample data [133].”
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“Since the loadings, Cronbach’s α, and the average variances extracted are all above recommended thresholds, the factors hold acceptable convergent validity (McDonald & Ho, 2002).”
Background
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“In order to compare the different theoretical models, chi-squared difference tests were conducted (R. McDonald & Ho, 2002).”
Method
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13 Structural Equation Modeling
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“To sum up from previous studies and reviews (Boomsma, 2000; Hooper, Coughlan, & Mullen, 2008; Hu & Bentler, 1999; Kline, 2005; McDonald & Ho, 2002), it was necessary to report indices of dispersed kinds, because there is no single “magic index” for all models and because different indices…”
Result
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Background
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“The recommendations for good fit are the following: χ2/DF ratios between one and three, values for RMSEA values less than .08 along with SRMR values less than .05, and GFI/CFI/NNFI values greater than .90 (Hu & Bentler, 1999; McDonald & Ho, 2002).”
Background
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“Values above .90 have traditionally been considered acceptable (Cheung & Rensvold, 2002; Kline, 1998; McDonald & Ho, 2002).”
Background
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Background
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“The Root Mean Square Error of Approximation (RMSEA) should be between .05 and .08 for an acceptable fit and .05 or less for a good fit (McDonald & Ho, 2002).”
Background
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“The model fit indices, using criteria described in McDonald and Ho (2002), showed excellent fit to the data (see Table 2).”
Method
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Background
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“However, studies have found that parameter estimates remain valid in SEM even when the data are not normal (see, McDonald & Ho, 2002), and therefore the CFA was undertaken using raw variables.”
Background
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“We conduct multi-group path analysis following the two-step approach as suggested by McDonald and Ho (2002) and McDonald (2010): i.e. examining the fit of our hypothesized path model and our measurement model separately.”
Method
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“stable CFA (McDonald and Ho, 2002).”
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“Specifically, these data could be influenced by stereotypes and social desirability (McDonald and Ho 2002).”
Background
[The social-cognitive model of achievement motivation in physical education].
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“The residual correlations (observed minus estimated polychoric correlations) were examined to assess specific areas of misfit (McDonald and Ho 2002).”
Background
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“To further investigate the relationship between burnout and depressive symptoms, we used the following procedure, in accordance with recommendations in McDonald (1999) and McDonald and Ho (2002).”
Method
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Ethical climate and missed nursing care in cancer care units
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Authors: McDonald, R. P., & Ho, M.-H. R.
Affiliations: University of Illinois Urbana-Champaign (US)
ORCID: Ho, Moon-Ho Ringo
Venue: Psychological Methods
Publisher: American Psychological Association (APA)
Published: 2002
Volume: 7
Issue: 1
Pages: 64-82
ISSN: 1082-989X (ISSN-L)
1939-1463
DOI: 10.1037/1082-989x.7.1.64
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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