Cited by 12,298Psychometric Methodologies and TestingStatistical Methods and Bayesian InferenceStatistical Distribution Estimation and Applications

The DOI matches its Crossref record; 64 of the 66 references it cites were found in a registry or an index.

Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification

Hu, Li-tze, Bentler, Peter M.·1998·Psychological Methods

DOI 10.1037/1082-989x.3.4.424

Open this paper in CoChat — free account

Abstract

This study evaluated the sensitivity of maximum likelihood (ML)-, generalized least squares (GLS)-, and asymptotic distribution-free (ADF)-based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustness theory also was ex-amined. Standardized root-mean-square residual (SRMR) was the most sensitive index to models with misspecified factor covariance(s), and Tucker-Lewis Index (1973; TLI), Bollen's fit index (1989; BL89), relative noncentrality index (RNI), comparative fit index (CFI), and the ML- and GLS-based gamma hat, McDonald's centrality index (1989; Me), and root-mean-square error of approximation (RMSEA) were the most sensitive indices to models with misspecified factor loadings. With ML and GLS methods, we recommend the use of SRMR, supple-mented by TLI, BL89, RNI, CFI, gamma hat, Me, or RMSEA (TLI, Me, and RMSEA are less preferable at small sample sizes). With the ADF method, we recommend the use of SRMR, supplemented by TLI, BL89, RNI, or CFI. Finally, most of the ML-based fit indices outperformed those obtained from GLS and ADF

Integrity signals

Registry

Crossref · 10.1037/1082-989x.3.4.424

Cites

64 of 64 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Self-citation
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
Comparative fit indexes in structural models.
Bentler, P. M. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.107.2.238 · Cited by 25,266
Self-citation
Significance tests and goodness of fit in the analysis of covariance structures.
Bentler, P. M., & Bonett, D. G. (1980) · Psychological Bulletin · doi:10.1037/0033-2909.88.3.588 · Cited by 20,015
Self-citation
Power analysis and determination of sample size for covariance structure modeling.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996) · Psychological Methods · doi:10.1037/1082-989x.1.2.130 · Cited by 10,418
EQS : structural equations program manual
Bentler, P. M. (1989) · Medical Entomology and Zoology · Cited by 9,669
Self-citation
Experimental Design: Procedures for the Behavioral Sciences
Kirk, R. (2013) · doi:10.4135/9781483384733 · Cited by 8,539
Testing Structural Equation Models.
Clogg, C. C., Bollen, K. A., & Long, J. S. (1995) · Social Forces · doi:10.2307/2580595 · Cited by 8,246
Untitled work
(1993) · Medical Entomology and Zoology · Cited by 7,690
A Reliability Coefficient for Maximum Likelihood Factor Analysis
Tucker, L. R., & Lewis, C. (1973) · Psychometrika · doi:10.1007/bf02291170 · Cited by 7,330

Show all 66 references

Sorted by citations

Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Self-citation
Convergent and discriminant validation by the multitrait-multimethod matrix.
Campbell, D. T., & Fiske, D. W. (1959) · Psychological Bulletin · doi:10.1037/h0046016 · Cited by 17,116
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
Cheung, G. W., & Rensvold, R. B. (2002) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem0902_5 · Cited by 16,280
The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000) · Cognitive Psychology · doi:10.1006/cogp.1999.0734 · Cited by 15,798
Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance
Chen, F. F. (2007) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1080/10705510701301834 · Cited by 12,217
Evaluating the use of exploratory factor analysis in psychological research.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.3.272 · Cited by 9,587
A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research
Vandenberg, R. J., & Lance, C. E. (2000) · Organizational Research Methods · doi:10.1177/109442810031002 · Cited by 7,997
Using pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173
In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler's (1999) Findings
Marsh, H. W., Hau, K.-T., & Wen, Z. (2004) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem1103_2 · Cited by 6,691
Scale Development Research: A Content Analysis and Recommendations for Best Practices
Worthington, R. L., & Whittaker, T. A. (2006) · The Counseling Psychologist · doi:10.1177/0011000006288127 · Cited by 4,087
Preliminary Psychometric Properties of the Acceptance and Action Questionnaire–II: A Revised Measure of Psychological Inflexibility and Experiential Avoidance
Bond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., Waltz, T., & Zettle, R. D. (2011) · Behavior Therapy · doi:10.1016/j.beth.2011.03.007 · Cited by 3,950
Specification, evaluation, and interpretation of structural equation models
Bagozzi, R. P., & Yi, Y. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0278-x · Cited by 3,735
Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014) · Organizational Research Methods · doi:10.1177/1094428114526928 · Cited by 3,332
The Positive and Negative Affect Schedule (PANAS): construct validity, measurement properties and normative data in a large non-clinical sample.
Crawford, J. R., & Henry, J. D. (2004) · British Journal of Clinical Psychology · doi:10.1348/0144665031752934 · Cited by 2,957
An empirical comparison of the efficacy of covariance-based and variance-based SEM
Reinartz, W., Haenlein, M., & Henseler, J. (2009) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2009.08.001 · Cited by 2,906
A Brief Guide to Structural Equation Modeling
Weston, R., & Gore, P. A. (2006) · The Counseling Psychologist · doi:10.1177/0011000006286345 · Cited by 2,718
Applications of Structural Equation Modeling in Psychological Research
MacCallum, R. C., & Austin, J. T. (2000) · Annual Review of Psychology · doi:10.1146/annurev.psych.51.1.201 · Cited by 2,634
Thanks coefficient alpha, we’ll take it from here.
McNeish, D. (2018) · Psychological Methods · doi:10.1037/met0000144 · Cited by 2,533
Psychometric properties of the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders–Fifth Edition (PCL-5) in veterans.
Bovin, M. J., Marx, B. P., Weathers, F. W., Gallagher, M. W., Rodriguez, P., Schnurr, P. P., & Keane, T. M. (2016) · Psychological Assessment · doi:10.1037/pas0000254 · Cited by 2,532
The relations among inhibition and interference control functions: A latent-variable analysis.
Friedman, N. P., & Miyake, A. (2004) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.133.1.101 · Cited by 2,309
Mediation analysis in partial least squares path modeling
Nitzl, C., Roldán, J. L., & Cepeda‐Carrión, G. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-07-2015-0302 · Cited by 2,818
Fearing the unknown: A short version of the Intolerance of Uncertainty Scale
Carleton, R. N., Norton, M. A. P. J., & Asmundson, G. J. G. (2007) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2006.03.014 · Cited by 2,288
The grateful disposition: A conceptual and empirical topography.
McCullough, M. E., Emmons, R. A., & Tsang, J.-A. (2002) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.82.1.112 · Cited by 3,664
Reporting practices in confirmatory factor analysis: an overview and some recommendations
Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009) · Psychological Methods · doi:10.1037/a0014694 · Cited by 2,242
Predicting green product consumption using theory of planned behavior and reasoned action
Paul, J., Modi, A., & Patel, J. (2016) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2015.11.006 · Cited by 2,399
Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-015-0455-4 · Cited by 2,111
The Sources of Four Commonly Reported Cutoff Criteria: What Did They Really Say?
Lance, C. E., Butts, M. M., & Michels, L. C. (2006) · Organizational Research Methods · doi:10.1177/1094428105284919 · Cited by 2,053
Academic self-efficacy and first year college student performance and adjustment.
Chemers, M. M., Hu, L.-T., & Garcia, B. F. (2001) · Journal of Educational Psychology · doi:10.1037/0022-0663.93.1.55 · Cited by 2,031
Self-citation
Robust dimensions of anxiety sensitivity: development and initial validation of the Anxiety Sensitivity Index-3
Taylor, S., Zvolensky, M. J., Cox, B. J., Deacon, B., Heimberg, R. G., Ledley, D. R., Abramowitz, J. S., Holaway, R. M., Sandin, B., Stewart, S. H., et al. (2007) · Psychological Assessment · doi:10.1037/1040-3590.19.2.176 · Cited by 1,866
Structural equations modeling: Fit Indices, sample size, and advanced topics
Iacobucci, D. (2010) · Journal of Consumer Psychology · doi:10.1016/j.jcps.2009.09.003 · Cited by 2,263
Estimation issues with PLS and CBSEM: Where the bias lies!
Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2016.06.007 · Cited by 1,991
Theories of reasoned action and planned behavior as models of condom use: A meta-analysis.
Albarracín, D., Johnson, B. T., Fishbein, M., & Muellerleile, P. A. (2001) · Psychological Bulletin · doi:10.1037/0033-2909.127.1.142 · Cited by 1,806
Partial least squares structural equation modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017) · Handbook of Market Research · doi:10.1007/978-3-319-05542-8_15-1 · Cited by 3,285
The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions.
Mackenzie, S. B., Podsakoff, P., & Jarvis, C. (2005) · Journal of Applied Psychology · doi:10.1037/0021-9010.90.4.710 · Cited by 1,819
Power and sensitivity of alternative fit indices in tests of measurement invariance.
Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008) · Journal of Applied Psychology · doi:10.1037/0021-9010.93.3.568 · Cited by 1,668
Individual differences in executive functions are almost entirely genetic in origin.
Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P., & Hewitt, J. K. (2008) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.137.2.201 · Cited by 1,547
Professional competence of teachers: Effects on instructional quality and student development.
Kunter, M., Klusmann, U., Baumert, J., Richter, D., Voss, T., & Hachfeld, A. (2013) · Journal of Educational Psychology · doi:10.1037/a0032583 · Cited by 1,553
An Empirical Evaluation of the Use of Fixed Cutoff Points in RMSEA Test Statistic in Structural Equation Models
Chen, F., Curran, P. J., Bollen, K. A., Kirby, J., & Paxton, P. (2008) · Sociological Methods & Research · doi:10.1177/0049124108314720 · Cited by 1,538
Modeling the antecedents of proactive behavior at work.
Parker, S. K., Williams, H. M., & Turner, N. (2006) · Journal of Applied Psychology · doi:10.1037/0021-9010.91.3.636 · Cited by 2,006
Impact on mental health and perceptions of psychological care among medical and nursing staff in Wuhan during the 2019 novel coronavirus disease outbreak: A cross-sectional study
Kang, L., Ma, S., Chen, M., Yang, J., Wang, Y., Li, R., Yao, L., Bai, H., Cai, Z., Xiang Yang, B., et al. (2020) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2020.03.028 · Cited by 1,516
Constructing validity: New developments in creating objective measuring instruments.
Clark, L. A., & Watson, D. (2019) · Psychological Assessment · doi:10.1037/pas0000626 · Cited by 1,470
How to factor-analyze your data right: do’s, don’ts, and how-to’s.
Matsunaga, M. (2010) · International journal of psychological research · doi:10.21500/20112084.854 · Cited by 1,431
A 6-Item Scale for Overall, Emotional, and Social Loneliness: Confirmatory Tests on Survey Data
Gierveld, J. D. J., & Tilburg, T. V. (2006) · Research on Aging · doi:10.1177/0164027506289723 · Cited by 1,467
Not All Executive Functions Are Related to Intelligence
Friedman, N. P., Miyake, A., Corley, R. P., Young, S. E., DeFries, J. C., & Hewitt, J. K. (2006) · Psychological Science · doi:10.1111/j.1467-9280.2006.01681.x · Cited by 1,293
On the Performance of Maximum Likelihood Versus Means and Variance Adjusted Weighted Least Squares Estimation in CFA
Beauducel, A., & Herzberg, P. Y. (2006) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1207/s15328007sem1302_2 · Cited by 1,390
A Multicomponent Conceptualization of Authenticity: Theory and Research
Kernis, M. H., & Goldman, B. M. (2006) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(06)38006-9 · Cited by 1,244
Model fit and model selection in structural equation modeling.
West, S. G., Taylor, A. B., & Wu, W. (2012) · Cited by 1,232
Evaluating Cutoff Criteria of Model Fit Indices for Latent Variable Models with Binary and Continuous Outcomes
Angeles, L. (2002) · Cited by 1,182
Development and initial validation of the COVID Stress Scales
Taylor, S., Landry, C. A., Paluszek, M. M., Fergus, T. A., McKay, D., & Asmundson, G. J. G. (2020) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2020.102232 · Cited by 1,169
Developmental cascades: Linking academic achievement and externalizing and internalizing symptoms over 20 years
Masten, A. S., Roisman, G. I., Long, J. D., Burt, K. B., Obradović, J., Riley, J. R., Boelcke-Stennes, K., & Tellegen, A. (2005) · Developmental Psychology · doi:10.1037/0012-1649.41.5.733 · Cited by 1,152
How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis.
Miyake, A., Friedman, N. P., Rettinger, D. A., Shah, P., & Hegarty, M. (2001) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.130.4.621 · Cited by 1,139
Achievement Emotions and Academic Performance: Longitudinal Models of Reciprocal Effects
Pekrun, R., Lichtenfeld, S., Marsh, H. W., Murayama, K., & Goetz, T. (2017) · Child Development · doi:10.1111/cdev.12704 · Cited by 1,091
Early adolescents' perceptions of the classroom social environment, motivational beliefs, and engagement.
Patrick, H., Ryan, A. M., & Kaplan, A. (2007) · Journal of Educational Psychology · doi:10.1037/0022-0663.99.1.83 · Cited by 1,085
TEACHER’S CORNER: Testing Measurement Invariance of Second-Order Factor Models
Chen, F. F., Sousa, K. H., & West, S. G. (2005) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem1203_7 · Cited by 1,032
Development of a Multi-Dimensional Scale for Measuring the Perceived Value of a Service
Petrick, J. F. (2002) · Journal of Leisure Research · doi:10.1080/00222216.2002.11949965 · Cited by 1,041
Relationship between innovativeness, quality, growth, profitability, and market value
Cho, H.-J., & Pucik, V. (2005) · Strategic Management Journal · doi:10.1002/smj.461 · Cited by 1,062
Psychometric Properties of the Five Facet Mindfulness Questionnaire in Depressed Adults and Development of a Short Form
Bohlmeijer, E., ten Klooster, P. M., Fledderus, M., Veehof, M., & Baer, R. (2011) · Assessment · doi:10.1177/1073191111408231 · Cited by 990
Online Social Networks: Why We Disclose
Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010) · Journal of Information Technology · doi:10.1057/jit.2010.6 · Cited by 1,022
Structural Equation Modeling in Marketing: Some Practical Reminders
Chin, W. W., Peterson, R. A., & Brown, S. P. (2008) · The Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679160402 · Cited by 1,044
Current Methodological Considerations in Exploratory and Confirmatory Factor Analysis
Schmitt, T. A. (2011) · Journal of Psychoeducational Assessment · doi:10.1177/0734282911406653 · Cited by 995
Use of structural equation modeling in operations management research: Looking back and forward ☆
Shah, R., & Goldstein, S. (2006) · Journal of Operations Management · doi:10.1016/j.jom.2005.05.001 · Cited by 1,083
Impact of lean manufacturing and environmental management on business performance: An empirical study of manufacturing firms
Yang, M. G., Hong, P. C., & Modi, S. B. (2010) · International Journal of Production Economics · doi:10.1016/j.ijpe.2010.10.017 · Cited by 1,018
In search of underlying dimensions: The use (and abuse) of factor analysis in Personality and Social Psychology Bulletin
Russell, D. W. (2002) · Personality and Social Psychology Bulletin · doi:10.1177/014616702237645 · Cited by 954
Stability and change of personality across the life course: The impact of age and major life events on mean-level and rank-order stability of the Big Five.
Specht, J., Egloff, B., & Schmukle, S. C. (2011) · Journal of Personality and Social Psychology · doi:10.1037/a0024950 · Cited by 1,318
The perseverative thinking questionnaire (PTQ): validation of a content-independent measure of repetitive negative thinking.
Ehring, T., Zetsche, U., Weidacker, K., Wahl, K., Schönfeld, S., & Ehlers, A. (2011) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2010.12.003 · Cited by 888
The Servant Leadership Survey: Development and Validation of a Multidimensional Measure
van Dierendonck, D., & Nuijten, I. (2011) · Journal of Business and Psychology · doi:10.1007/s10869-010-9194-1 · Cited by 1,096
“The generally accepted values of good fit are close to .95 for the CFI and the TLI, and less than .08 for the SRMR and RMSEA (Fan and Sivo 2007; Hu and Bentler 1998 ).”
Method
A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models
Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005) · Journal of Business Research · doi:10.1016/j.jbusres.2003.10.007 · Cited by 906
Structural Equation Modeling: Strengths, Limitations, and Misconceptions
Tomarken, A. J., & Waller, N. G. (2004) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.1.102803.144239 · Cited by 946
Dimensions of Cruisers’ Experiences, Satisfaction, and Intention to Recommend
Hosany, S., & Witham, M. (2009) · Journal of Travel Research · doi:10.1177/0047287509346859 · Cited by 948
The job demands-resources model: A meta-analytic review of longitudinal studies
Lesener, T., Gusy, B., & Wolter, C. (2018) · Work & Stress · doi:10.1080/02678373.2018.1529065 · Cited by 1,116
Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era
Baz, J. E., & Ruel, S. (2020) · International Journal of Production Economics · doi:10.1016/j.ijpe.2020.107972 · Cited by 968
The development and initial validation of the cognitive fusion questionnaire
Gillanders, D. T., Bolderston, H., Bond, F. W., Dempster, M., Flaxman, P. E., Campbell, L., Kerr, S., Tansey, L., Noel, P., Ferenbach, C., et al. (2014) · Behavior Therapy · doi:10.1016/j.beth.2013.09.001 · Cited by 837
The Roles of Quality, Value, and Satisfaction in Predicting Cruise Passengers’ Behavioral Intentions
Petrick, J. F. (2004) · Journal of Travel Research · doi:10.1177/0047287504263037 · Cited by 879
Specificity of cognitive emotion regulation strategies: a transdiagnostic examination
Aldao, A., & Nolen-Hoeksema, S. (2010) · Behaviour Research and Therapy · doi:10.1016/j.brat.2010.06.002 · Cited by 860
Structural Equation Modeling: Reviewing the Basics and Moving Forward
Ullman, J. B. (2006) · Journal of Personality Assessment · doi:10.1207/s15327752jpa8701_03 · Cited by 935
A dissociation between mental rotation and perspective-taking spatial abilities
Hegarty, M. (2004) · Intelligence · doi:10.1016/j.intell.2003.12.001 · Cited by 860
A Bifactor Exploratory Structural Equation Modeling Framework for the Identification of Distinct Sources of Construct-Relevant Psychometric Multidimensionality
Morin, A. J. S., Arens, A. K., & Marsh, H. W. (2015) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2014.961800 · Cited by 913
Motivation in online learning: testing a model of self-determination theory
Chen, K.-C., & Jang, S.-J. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.01.011 · Cited by 955
Increasingly certain about uncertainty: Intolerance of uncertainty across anxiety and depression
Carleton, R. N., Mulvogue, M. K., Thibodeau, M. A., McCabe, R. E., Antony, M. M., & Asmundson, G. J. G. (2012) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2012.01.011 · Cited by 775
Destination Personality: An Application of Brand Personality to Tourism Destinations
Ekinci, Y., & Hosany, S. (2006) · Journal of Travel Research · doi:10.1177/0047287506291603 · Cited by 815
Low self-esteem prospectively predicts depression in adolescence and young adulthood.
Orth, U., Robins, R. W., & Roberts, B. W. (2008) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.95.3.695 · Cited by 784
Dimensions of Tourists’ Emotional Experiences Towards Hedonic Holiday Destinations
Hosany, S., & Gilbert, D. (2009) · Journal of Travel Research · doi:10.1177/0047287509349267 · Cited by 846
Impact of knowledge management practices on green innovation and corporate sustainable development: A structural analysis
Abbas, J., & Sağsan, M. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.05.024 · Cited by 826
Examining the effects of contextual factors on TQM and performance through the lens of organizational theories: An empirical study
Sila, I. (2006) · Journal of Operations Management · doi:10.1016/j.jom.2006.02.003 · Cited by 788
The role of gratitude in the development of social support, stress, and depression: two longitudinal studies
Wood, A. M., Maltby, J., Gillett, R., Linley, P. A., & Joseph, S. (2008) · Journal of Research in Personality · doi:10.1016/j.jrp.2007.11.003 · Cited by 761
Psychological Need Thwarting in the Sport Context: Assessing the Darker Side of Athletic Experience
Bartholomew, K. J., Ntoumanis, N., Ryan, R. M., & Thøgersen‐Ntoumani, C. (2011) · Journal of Sport and Exercise Psychology · doi:10.1123/jsep.33.1.75 · Cited by 847
On the emancipation of PLS-SEM: a commentary on Rigdon (2012)
Sarstedt, M., Ringle, C. M., Henseler, J., & Hair, J. F. (2014) · Long Range Planning · doi:10.1016/j.lrp.2014.02.007 · Cited by 758
Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research
Chin, W. W., Cheah, J., Liu, Y., Ting, H., Lim, X., & Cham, T. (2020) · Industrial Management & Data Systems · doi:10.1108/imds-10-2019-0529 · Cited by 876
First- and Second-Generation College Students: A Comparison of Their Engagement and Intellectual Development
Pike, G. R., & Kuh, G. D. (2005) · The Journal of Higher Education · doi:10.1080/00221546.2005.11772283 · Cited by 781
The childhood trauma questionnaire in a community sample: Psychometric properties and normative data
Scher, C. D., Stein, M. B., Asmundson, G. J. G., McCreary, D. R., & Forde, D. R. (2001) · Journal of Traumatic Stress · doi:10.1023/a:1013058625719 · Cited by 759
The Role of Chronic Peer Difficulties in the Development of Children's Psychological Adjustment Problems
Ladd, G. W., & Troop-Gordon, W. (2003) · Child Development · doi:10.1111/1467-8624.00611 · Cited by 717
The Structure of Goal Contents Across 15 Cultures.
Grouzet, F. M. E., Kasser, T., Ahuvia, A., Dols, J. M. F., Kim, Y., Lau, S., Ryan, R. M., Saunders, S. A., Schmuck, P., & Sheldon, K. M. (2005) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.89.5.800 · Cited by 795
Consumer Self-Confidence: Refinements in Conceptualization and Measurement
Bearden, W. O., Hardesty, D. M., & Rose, R. L. (2001) · Journal of Consumer Research · doi:10.1086/321951 · Cited by 733
The Role of Acceptance and Job Control in Mental Health, Job Satisfaction, and Work Performance
Bond, F. W., & Bunce, D. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.6.1057 · Cited by 711
Confirmatory factor analyses of posttraumatic stress symptoms in deployed and nondeployed veterans of the Gulf War.
Simms, L. J., Watson, D., & Doebbeling, B. N. (2002) · Journal of Abnormal Psychology · doi:10.1037//0021-843x.111.4.637 · Cited by 699
Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model
Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120880 · Cited by 825
The De Jong Gierveld short scales for emotional and social loneliness: tested on data from 7 countries in the UN generations and gender surveys
De Jong Gierveld, J., & Van Tilburg, T. (2010) · European Journal of Ageing · doi:10.1007/s10433-010-0144-6 · Cited by 791
How teachers’ self-efficacy is related to instructional quality: A longitudinal analysis.
Holzberger, D., Philipp, A., & Kunter, M. (2013) · Journal of Educational Psychology · doi:10.1037/a0032198 · Cited by 853
Spatial abilities at different scales: Individual differences in aptitude-test performance and spatial-layout learning
Hegarty, M., Montello, D. R., Richardson, A. E., Ishikawa, T., & Lovelace, K. (2006) · Intelligence · doi:10.1016/j.intell.2005.09.005 · Cited by 820
Psychometric evaluation of the altered states of consciousness rating scale (OAV)
Studerus, E., Gamma, A., & Vollenweider, F. X. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012412 · Cited by 683

Authors: Hu, L.-T., & Bentler, P. M.
Affiliations: University of California, Santa Cruz (US)
ORCID: Bentler, Peter M.
Venue: Psychological Methods
Publisher: American Psychological Association (APA)
Published: 1998-12
Volume: 3
Issue: 4
Pages: 424-453
ISSN: 1082-989X (ISSN-L)
1939-1463
DOI: 10.1037/1082-989x.3.4.424
OpenAlex: W2005092827
Semantic Scholar: a92c9726361d9c1d165dbf2ea781b6c48363a816
Cited by: 12,298
References: 66
Citations by year: 2026: 639 · 2025: 1003 · 2024: 1076 · 2023: 1094 · 2022: 934 · 2021: 884 · 2020: 738 · 2019: 665 · 2018: 600 · 2017: 512 · 2016: 465 · 2015: 450 · 2014: 474 · 2013: 433 · 2012: 386
FWCI: 43.57
Type: journal article
Language: en
Open access: closed
Locations: Psychological Methods (publishedVersion)
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 Distribution Estimation and Applications
Keywords: model fit indices, model misspecification, structural equation modeling, comparative fit index, RMSEA, asymptotic robustness, factor loadings, sample size, distributional assumptions

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks