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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Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives
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“In this situation, SRMR is the preferred fit index (see Hu & Bentler, 1999; Iacobucci, 2010; Kenny, Kaniskan, & McCoach, 2011).”
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“that observed in the data (Iacobucci 2010).”
Big Data Analytics in Genomics
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“100 SNPs are randomly selected from the yeast eQTL dataset [56].”
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“Two criteria indicating acceptable model fit, CFI (comparative fit index) ≥ 0.95 and SRMR (standardized root mean square residual) ≤ 0.09, are recommended (Iacobucci 2010).”
MethodInfluential
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Improving physician clinical documentation quality: evaluating two self-efficacy-based training programs.
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“Similarly, Iacobucci (2010) encouraged researchers to not take the rules of thumb regarding model fit index cutoff points too seriously, but rather to ‘‘ask good theoretical questions: Is every hypothesized link logically supported, and is there a sound, comprehensive yet parsimonious theoretical story for the entire…”
Background
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Environmental perceptions, self-regulation, and coping with noise mediate the associations between children's physical environment and sleep and mental health problems.
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“To indicate a good model fit (Hooper et al., 2007; Iacobucci, 2010), the χ 2 / df should not exceed 3; the robust CFI and TLI should be 0.90 or higher; and the RMSEA and SRMR should not exceed 0.08.”
Influential
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“While various recommendations exist for determining sample size in SEM studies (Gefen et al., 2000; Boomsma and Hoogland, 2001; Hoe, 2008; Iacobucci, 2010), we determined 24 free parameters in this study and a minimum sample size of 120 mother–infant dyads.”
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“Moreover, it is essential to authenticate the sample size required to develop a good structural model (Iacobucci, 2010).”
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“The latent variable model showed a good model fit for both the prenatal and postnatal period (Iacobucci, 2010): prenatal model: chi- square statistics (χ2) (2) = 7.42, p = .024, standardized root mean square residual (SRMR) = .013, and comparative fit index (CFI) = .995.”
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“Sample size was determined for the path analysis model based upon previous simulation studies which indicate that simple structural equation models, which path analysis falls under the umbrella of, with reliable measures, good fit indices, and limited missing data will converge with sample sizes around 100 (Iacobucci,…”
Method
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“Although the data is relatively small, because this research uses The partial least squares structural equation modeling (PLS-SEM) analysis, the number of sample data can work well [51].”
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“In addition, the model to be tested using SEM is not overly complex and source of data is very reliable in this study, so the sample size of 209 can be enough [80].”
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“Following Iacobucci (2009, 2010), we relied on the correlation matrices for the confirmatory factor analysis.”
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“As Iacobucci (2010) states, “as N increases, χ2 blows up,” with quasiexponential gains in the χ2 statistic reached for sample sizes as low as 500.”
Background
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“In addition, only the models with the smallest sample 2 size ( 600), brand name knowledge and cigarette price among current smokers, met the χ2/d.f. 3 threshold, which is also sensitive to sample size (Iacobucci, 2010).”
Background
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“In addition, it has been recommended that using the ratio of N to the number of free parameters in a model can provide an adequate sample size for factor analysis and structural equation modeling (Bentler & Chou, 1987; Iacobucci, 2010; Myers, Ahn, & Jin, 2011).”
BackgroundMethod
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“SEM is a progression from factor analysis, ANOVA, and regression (Byrne, 1998; Iacobucci, 2010; Lei & Wu, 2007), which allows the measurement of complex relationships between a set of independent and dependent variables (Hoyle, 2012).”
BackgroundMethodInfluential
Lessons from the global financial crisis for the semiconductor industry
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“PLS is a common multivariate analytical approach, and is robust to sample size and distributional assumptions of the underlying variables (Iacobucci, 2010).”
Background
A succinct rating scale for radiology report quality
Yang, C., Kasales, C. J., Ouyang, T., Peterson, C., Sarwani, N., Tappouni, R., & Bruno, M. A. (2014) · SAGE Open Medicine · doi:10.1177/2050312114563101 · Cited by 15

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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