Behavior of descriptive fit indexes in confirmatory factor analysis using ordered categorical data

References

• Anderson , J. C. and Gerbing , D. W. 1984 . The effect of sampling error on convergence, improper solutions, and goodness‐of‐fit indices for maximum likelihood confirmatory factor analyses . Psychometrika , 49 : 155 – 173 .
   Web of Science ®Google Scholar
• Babakus , E. , Ferguson , C. E. and Jöreskog , K. G. 1987 . The sensitivity of confirmatory maximum likelihood factor analysis to violations of measurement scale and distributional assumptions . Journal of Marketing Research , 29 : 222 – 228 .
   Google Scholar
• Bentler , P. M. 1990 . Comparative fit indexes in structural models . Psychological Bulletin , 107 : 238 – 246 .
   PubMed Web of Science ®Google Scholar
• Bentler , P. M. and Bonett , D. G. 1980 . Significance tests and goodness of fit in the analysis of covariance structures . Psychological Bulletin , 88 : 588 – 606 .
   Web of Science ®Google Scholar
• Bollen , K. A. 1986 . Sample size and Bentler and Bonett's non‐normed fit index . Psychometrika , 51 : 375 – 377 .
   Web of Science ®Google Scholar
• Bollen , K. A. 1989 . A new incremental fit index for general structural equation models . Sociological Methods and Research , 17 : 303 – 316 .
   Web of Science ®Google Scholar
• Bollen , K. A. 1990 . Overall fit in covariance structure models: Two types of sample size effects . Psychological Bulletin. , 107 : 256 – 259 .
   Web of Science ®Google Scholar
• Bollen , K. A. and Liang , J. 1988 . Some properties of Hoelter's CN . Sociological Methods & Research , 16 : 492 – 503 .
   Web of Science ®Google Scholar
• Boomsma , A. 1987 . “ The robustness of maximum likelihood estimation in structural equation models ” . In Structural modeling by example: Applications in educational, sociological, and behavioral research , Edited by: Cuttance , P. and Ecob , R. Cambridge, , England : Cambridge University Press .
   Google Scholar
• Browne , M. W. 1984 . Asymptotically distribution‐free methods for the analysis of covariance structures . British Journal of Mathematical and Statistical Psychology , 37 : 62 – 83 .
   PubMed Web of Science ®Google Scholar
• Browne , M. W. and Cudeck , R. 1993 . “ Alternative ways of assessing model fit ” . In Testing structural equation models , Edited by: Bollen , K. A. and Long , J. S. 136 – 162 . Newbury Park, CA : Sage .
   Google Scholar
• Chou , C‐P. , Bentler , P. M. and Satorra , A. 1991 . Scale test statistics and robust standard errors for non‐normal data in covariance structure analysis: A Monte Carlo study . British Journal of Mathematical and Statistical Psychology , 44 : 347 – 357 .
   PubMed Web of Science ®Google Scholar
• Ding , L. , Velicer , W. R. and Harlow , L. L. 1995 . Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices . Structural Equation Modeling , 2 : 119 – 144 .
   Web of Science ®Google Scholar
• 1995 . Excel 5.0 [Computer software] , Seattle, WA : Microsoft Corporation .
   Google Scholar
• Gerbing , D. W. and Anderson , J. C. 1993 . “ Monte Carlo evaluations of goodness‐of‐fit indices for structural equation models ” . In Testing structural equation models , Edited by: Bollen , K. A. and Long , J. S. 40 – 65 . Newbury Park, CA : Sage .
   Google Scholar
• Hoelter , J. W. 1983 . The analysis of covariance structures: Goodness‐of‐fit indices . Sociological Methods & Research , 11 : 325 – 344 .
   Web of Science ®Google Scholar
• Hu , L. and Bentler , P. M. 1995 . “ Evaluating model fit ” . In Structural equation modeling: Concepts, issues, and applications , Edited by: Hoyle , R. H. 76 – 99 . Thousand Oaks, CA : Sage .
   Google Scholar
• Hu , L. , Bentler , P. M. and Kano , Y. 1992 . Can test statistics in covariance structure analysis be trusted? . Psychological Bulletin , 112 : 351 – 362 .
   PubMed Web of Science ®Google Scholar
• Hutchinson , S. R. 1993 . The stability of post hoc model modifications and measures of fit in covariance structure models , Athens : University of Georgia . Unpublished doctoral dissertation
   Google Scholar
• Jöreskog , K. G. 1990 . New developments in LISREL: Analysis of ordinal variables using polychoric correlations and weighted least squares . Quality and Quantity , 24 : 387 – 404 .
   Web of Science ®Google Scholar
• Jöreskog , K. G. and Sörbom , D. 1981 . LISREL V: Analysis of linear structural relationships by maximum likelihood and least squares methods , Chicago : International Educational Services .
   Google Scholar
• Jöreskog , K. G. and Sörbom , D. 1993a . LISREL 8 user's reference guide , Chicago : Scientific Software International .
   Google Scholar
• Jöreskog , K. G. and Sörbom , D. 1993b . PRELIS 2 user's reference guide , Chicago : Scientific Software International .
   Google Scholar
• LaDu , T. J. and Tanaka , J. S. 1989 . The influence of sample size, estimation method, and model specification on goodness‐of‐fit assessments in structural equation models . Journal of Applied Psychology , 74 : 625 – 635 .
   Web of Science ®Google Scholar
• LaDu , T. J. and Tanaka , J. S. 1995 . Incremental fit index changes for nested structural equation models . Multivariate Behavioral Research , 30 : 289 – 316 .
   PubMed Web of Science ®Google Scholar
• Marsh , H. W. , Baila , J. R. and McDonald , R. P. 1988 . Goodness‐of‐fit indexes in confirmatory factor analysis: The effect of sample size . Psychological Bulletin , 103 : 391 – 410 .
   Web of Science ®Google Scholar
• McDonald , R. P. 1989 . An index of goodness‐of‐fit based on non‐centrality . Journal of Classification , 6 : 97 – 103 .
   Web of Science ®Google Scholar
• McDonald , R. P. and Marsh , H. W. 1990 . Choosing a multivariate model: Non‐centrality and goodness of fit . Psychological Bulletin , 107 : 247 – 255 .
   Web of Science ®Google Scholar
• Mulaik , S. A. , James , L. R. , Van Alstine , J. , Bennet , N. , Lind , S. and Stillwell , C. D. 1989 . Evaluation of goodness‐of‐fit indices for structural equation models . Psychological Bulletin , 105 : 430 – 445 .
   Web of Science ®Google Scholar
• Muthén , B. 1984 . A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators . Psychometrika , 49 : 115 – 132 .
   Web of Science ®Google Scholar
• Muthén , B. and Kaplan , D. 1985 . A comparison of some methodologies for the factor analysis of non‐normal Likert variables . British Journal of Mathematical and Statistical Psychology , 38 : 171 – 189 .
   Web of Science ®Google Scholar
• Muhén , B. and Kaplan , D. 1992 . A comparison of some methodologies for the factor analysis of non‐normal Likert variables: A note on the size of the model . British Journal of Mathematical and Statistical Psychology , 45 : 19 – 30 .
   Web of Science ®Google Scholar
• Potthast , M. J. 1993 . Confirmatory factor analysis of ordered categorical variables with large models . British Journal of Mathematical and Statistical Psychology , 46 : 273 – 286 .
   Web of Science ®Google Scholar
• Sharma , S. , Durvasula , S. and Dillon , W. R. 1989 . Some results on the behavior of alternate covariance structure estimation procedures in the presence of non‐normal data . Journal of Marketing Research , 26 : 214 – 221 .
   Web of Science ®Google Scholar
• Steiger , J. H. 1990 . Structural model evaluation and modification: An interval estimation approach . Multivariate Behavioral Research , 25 : 173 – 180 .
   PubMed Web of Science ®Google Scholar
• Tanaka , J. S. 1993 . “ Multifaceted conceptions of fit in structural equation models ” . In Testing structural equation models , Edited by: Bollen , K. A. and Long , J. S. 10 – 39 . Newbury Park, CA : Sage .
   Google Scholar
• Tippets , E. A. 1991 . A comparison of methods for evaluating and modifying covariance structure models , College Park : University of Maryland . Unpublished doctoral dissertation
   Google Scholar
• Waag , L. , Fan , X. and Willson , V. L. 1996 . Effects of non‐normal data on parameter estimates and fit indices for a model with latent and manifest variables: An empirical study . Structural Equation Modeling , 3 : 228 – 247 .
   Web of Science ®Google Scholar