Cited by 2,263Psychometric Methodologies and TestingStatistical Methods and Bayesian InferenceStatistical Methods and Applications

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Structural equations modeling: Fit Indices, sample size, and advanced topics

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Iacobucci, Dawn·2010·Journal of Consumer Psychology

DOI 10.1016/j.jcps.2009.09.003

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Abstract

This article is the second of two parts intended to serve as a primer for structural equations models for the behavioral researcher. The first article introduced the basics: the measurement model, the structural model, and the combined, full structural equations model. In this second article, advanced issues are addressed, including fit indices and sample size, moderators, longitudinal data, mediation, and so forth.

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“…the survey was very low compared to the average duration of 13.1 min), 154 answers could be used for the subsequent steps (response rate: 20%); a number that is assessed as suitable sample size (Anderson & Gerbing, 1984) and that is a “convergent and proper solution” (Iacobucci, 2010, p. 92).”
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Embedding cognizance in intellectual development.
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“Maximum likelihood is preferred because it is proven to be robust against violation of normality assumptions (Iacobucci, 2010).”
Background
On the Examination of Longitudinal Trends Between Teacher–Student Relationship Quality and Social Skills During Elementary School
Hajovsky, D. B., Chesnut, S. R., Helbig, K. A., & Goranowski, S. M. (2021) · School psychology review · doi:10.1080/2372966x.2021.1883995 · Cited by 34
“RMSEA estimates less than 0.08, CFI and TLI estimates greater than 0.90, and SRMR estimates less than 0.10 indicate acceptable model fit to the data (Cangur & Ercan, 2015; Iacobucci, 2010; Little, 2013).”
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“Following propositions in the literature, the cut-off value for CFI was 0.95, for SRMR values close to 0.08 were accepted (Hu & Bentler, 1999, p. 27; Iacobucci, 2010, p. 92).”
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“A nonsignificant chi-square test would indicate that the model fits the data well [29].”
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“To confirm model-data fit, preliminary fit criteria, overall model fit, and fit of internal structure of models were tested, using Root Mean Square Error of Approximation (RMSEA;Steiger, 1990; Iacobucci, 2010), Normed Fit Index (NFI;Bentler & Bonett, 1980; Marcoulides & Schumacker, 2013), Comparative Fit Index (CFI;Be…”
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“It has been suggested that these cut-offs should not be taken literally and that the estimation of model fit should consider these indices as a whole (e.g. Iacobucci, 2010; Steiger, 2000).”
Background
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“The maximum likelihood method (ML) was used to estimate the models, because compared to other estimation methods, ML generally performs best (Iacobucci 2010).”
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“One of these measures is the normed chi-square ( χ 2 /df), where a ratio between 2 and 5 is considered acceptable [6, 15, 16].”
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“Estimation of model fit was assessed through chi-squared test, root mean square error of approximation (RMSEA), confirmatory fit index (CFI), and standardized root mean square residual (SRMR).(68,69) Logistic regression analysis was performed to identify the association of baseline clinical outcomes and engagement wit…”
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“Although structural equation modeling does not provide an accurate sample size standard, Dawn Iacobucci (2010) recommends a sample size of 200 or more [38].”
Background
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“This led to a unifactorial model with good model fit (χ2 [2] = 7.67, p = 0.02; χ2/df = 3.83; CFI = 1.00; RMSEA= 0.04; PCLOSE = 0.597; SRMR= 0.01; Iacobucci 2010).”
Influential
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“Regarding sample size, Iacobucci (2010) stated that when the model is not overly complex, the expected effects sizes are large and the variables are reliable, rather small sample sizes would be sufficient.”
Background
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“…out that the “‘conventional’ rules of thumb about acceptable fit are too restrictive (even though there has been a recent push for even stricter standards)” (Marsh, Hau, & Wen, 2004, p. 325) and that it is unnecessary to “be overly critical if the CFI is not quite 0.95” (Iacobucci, 2010, p. 95).”
BackgroundInfluential
Association between rumination factors and eating disorder behaviours in young women
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“N < 250; Hu & Bentler, 1999; Kenny & McCoach, 2003) and that SRMR is preferred in this case as it is less sensitive to small sample size (Iacobucci, 2010).”
Background
A Measurement Scale for Evaluating Quality of Work Life: Conceptualization and Empirical Validation
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“This analysis conceptualizes employees’ QWL as an attitude since the operation of measures on attitudes is more consistent with the reflective analysis (Iacobucci, 2010).”
Result
Psychometric properties of the Obsessive-Compulsive Inventory Revised in African Americans with and without obsessive-compulsive disorder
Williams, M. T., Davis, D. M., Thibodeau, M. A., & Bach, N. (2013) · Journal of Obsessive-Compulsive and Related Disorders · doi:10.1016/j.jocrd.2013.07.003 · Cited by 33
“supports the applicability of CFAs in samples of this size (Iacobucci, 2010).”
BackgroundMethodInfluential

Authors: Iacobucci, D.
Affiliations: Vanderbilt University (US)
Corresponding author: Iacobucci, Dawn
ORCID: Iacobucci, Dawn
Venue: Journal of Consumer Psychology
Publisher: Wiley
Published: 2009-10-03
Volume: 20
Issue: 1
Pages: 90-98
ISSN: 1057-7408 (ISSN-L)
1532-7663
DOI: 10.1016/j.jcps.2009.09.003
OpenAlex: W2038318317
Cited by: 2,263
References: 0
Citations by year: 2026: 111 · 2025: 193 · 2024: 193 · 2023: 186 · 2022: 210 · 2021: 208 · 2020: 158 · 2019: 193 · 2018: 169 · 2017: 129 · 2016: 128 · 2015: 123 · 2014: 94 · 2013: 86 · 2012: 53
FWCI: 34.78
Type: journal article
Language: en
Open access: green
papers.ssrn.com
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Journal of Consumer Psychology (publishedVersion)
SSRN Electronic Journal (submittedVersion)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: structural equation modeling, model fit indices, sample size, moderators, longitudinal data, mediation, measurement model, structural model

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Structural equations modeling: Fit Indices, sample size, and advanced topics

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