REFERENCES
- Akaike , H. 1973 . “ Information theory and an extension of the maximum likelihood principle. ” . In Second international symposium on information theory Edited by: Petrov , B. N. and Csaki , F. 267 – 281 . Budapest , , Hungary : Akademia Kiado. .
- Akaike , H. 1987 . Factor analysis and AIC . Psychometrika , 52 : 317 – 332 .
- Bandalos , D. L. 1997 . Assessing sources of error in structural equation models: The effects of sample size, reliability, and model misspecification . Structural Equation Modeling , 4 : 177 – 192 .
- Bentler , P. M. 1980 . Multivariate analysis with latent variables: Causal modeling . Annual Review of Psychology , 31 : 419 – 456 .
- Bentler , P. M. and Mooijaart , A. 1989 . Choice of structural model via parsimony: A rationale based on precision . Psychological Bulletin , 106 : 315 – 317 .
- Bollen , K. A. 1989 . Structural equations with latent variables. New York , NY : Wiley. .
- Box , G. E. P. 1976 . Science and statistics . Journal of the American Statistical Association , 71 : 791 – 799 .
- Bozdogan , H. 2000 . Akaike's information criterion and recent developments in information complexity . Journal of Mathematical Psychology , 44 : 62 – 91 .
- Bozdogan , H. and Ramirez , D. E. 1987 . “ An expert model selection approach to determine the “best” pattern structure in factor analysis models. ” . In Multivariate statistical modeling and data analysis Edited by: Bozdogan , H. and Gupta , A. K. 35 – 60 . Dordrecht , , The Netherlands : D. Reidel. .
- Browne , M. W. 2000 . Cross-validation methods . Journal of Mathematical Psychology , 44 : 108 – 132 .
- Browne , M. W. 2001 . An overview of analytic rotation in exploratory factor analysis . Multivariate Behavioral Research , 36 : 111 – 150 .
- Browne , M. W. and Cudeck , R. 1989 . Single sample cross-validation indices for covariance structures . Multivariate Behavioral Research , 24 : 445 – 455 .
- Browne , M. W. and Cudeck , R. 1992 . Alternative ways of assessing model fit . Sociological Methods and Research , 21 : 230 – 258 .
- Browne , M. W. , Cudeck , R. , Tateneni , K. and Mels , G. 2008 . CEFA: Comprehensive exploratory factor analysis. Retrieved from http://faculty.psy.ohio-state.edu/browne/
- Burnham , K. P. and Anderson , D. R. 2004 . Multimodel inference: Understanding AIC and BIC in model selection . Sociological Methods & Research , 33 : 261 – 304 .
- Cattell , R. B. 1966 . The scree test for the number of factors . Multivariate Behavioral Research , 1 : 245 – 276 .
- Collyer , C. E. 1985 . Comparing strong and weak models by fitting them to computer-generated data . Perception and Psychophysics , 38 : 476 – 481 .
- Comrey , A. L. and Lee , H. B. 1992 . A first course in factor analysis, , 2nd ed. Hillsdale , NJ : Erlbaum. .
- Costa , P. T. Jr. and McCrae , R. R. 1992 . Normal personality assessment in clinical practice: The NEO Personality Inventory . Psychological Assessment , 4 : 5 – 13 .
- Cudeck , R. 1991 . “ Comments on “Using causal models to estimate indirect effects.”. ” . In Best methods for the analysis of change: Recent advances, unanswered questions, future directions Edited by: Collins , L. M. and Horn , J. L. 260 – 263 . Washington , DC : American Psychological Association. .
- Cudeck , R. and Henly , S. J. 1991 . Model selection in covariance structures analysis and the “problem” of sample size: A clarification . Psychological Bulletin , 109 : 512 – 519 .
- Cudeck , R. and Henly , S. J. 2003 . A realistic perspective on pattern representation in growth data: Comment on Bauer and Curran (2003) . Psychological Methods , 8 : 378 – 383 .
- Curran , P. J. , Bollen , K. A. , Chen , F. , Paxton , P. and Kirby , J. B. 2003 . Finite sampling properties of the point estimates and confidence intervals of the RMSEA . Sociological Methods & Research , 32 : 208 – 252 .
- Cutting , J. E. 2000 . Accuracy, scope, and flexibility of models . Journal of Mathematical Psychology , 44 : 3 – 19 .
- Cutting , J. E. , Bruno , N. , Brady , N. P. and Moore , C. 1992 . Selectivity, scope, and simplicity of models: A lesson from fitting judgments of perceived depth . Journal of Experimental Psychology: General , 121 : 364 – 381 .
- De Gooijer , J. G. 1995 . Cross-validation criteria for covariance structures . Communications in Statistics: Simulation and Computation , 24 : 1 – 16 .
- Dunn , J. C. 2000 . Model complexity: The fit to random data reconsidered . Psychological Research , 63 : 174 – 182 .
- Everett , J. E. 1983 . Factor comparability as a means of determining the number of factors and their rotation . Multivariate Behavioral Research , 18 : 197 – 218 .
- Eysenck , H. J. 1991 . Dimensions of personality: 16, 5, or 3? Criteria for a taxonomic paradigm . Personality and Individual Differences , 12 : 773 – 790 .
- Fabrigar , L. R. , Wegener , D. T. , MacCallum , R. C. and Strahan , E. J. 1999 . Evaluating the use of exploratory factor analysis in psychological research . Psychological Methods , 4 : 272 – 299 .
- Grünwald , P. D. 2000 . Model selection based on minimum description length . Journal of Mathematical Psychology , 44 : 133 – 152 .
- Heskes , T. 1998 . Bias/variance decomposition for likelihood-based estimators . Neural Computation , 10 : 1425 – 1433 .
- Hu , L. and Bentler , P. M. 1999 . Cutoff criteria in fix indexes in covariance structure analysis: Conventional criteria versus new alternatives . Structural Equation Modeling , 6 : 1 – 55 .
- Hubbard , R. and Allen , S. J. 1989 . On the number and nature of common factors extracted by the eigenvalue-one rule using BMDP vs. SPSSx . Psychological Reports , 65 : 155 – 160 .
- Humphreys , L. G. 1964 . Number of cases and number of factors: An example where N is very large . Educational and Psychological Measurement , 24 : 457 – 466 .
- Ichikawa , M. 1988 . Empirical assessments of AIC procedure for model selection in factor analysis . Behaviormetrika , 24 : 33 – 40 .
- Jessor , R. and Jessor , S. L. 1977 . Problem behavior and psychosocial development: A longitudinal study of youth. New York , NY : Academic Press. .
- Jessor , R. and Jessor , S. L. 1991 . Socialization of problem behavior in youth, 1969–1981 Cambridge , MA http://hdl.handle.net/1902.1/00782, UNF:3:bNvdfUO8c9YXemVwScJy/A==]. Henry A. Murray Research Archive (http://www.murray.harvard.edu/
- Leahy , K. 1994 . The overfitting problem in perspective . AI Expert , 9 : 35 – 36 .
- Linhart , H. and Zucchini , W. 1986 . Model selection. New York , NY : Wiley. .
- Lopes , H. F. and West , M. 2004 . Bayesian model assessment in factor analysis . Statistica Sinica , 14 : 41 – 67 .
- MacCallum , R. C. 2003 . Working with imperfect models . Multivariate Behavioral Research , 38 : 113 – 139 .
- MacCallum , R. C. , Browne , M. W. and Cai , L. 2007 . “ Factor analysis models as approximations: Some history and some implications. ” . In Factor analysis at 100: Historical developments and future directions Edited by: Cudeck , R. and MacCallum , R. C. 153 – 175 . Mahwah , NJ : Erlbaum. .
- MacCallum , R. C. , Browne , M. W. and Sugawara , H. M. 1996 . Power analysis and determination of sample size for covariance structure modeling . Psychological Methods , 1 : 130 – 149 .
- MacCallum , R. C. and Tucker , L. R. 1991 . Representing sources of error in the common factor model: Implications for theory and practice . Psychological Bulletin , 109 : 502 – 511 .
- McCrae , R. R. , Zonderman , A. B. , Costa , P. T. Jr. , Bond , M. H. and Paunonen , S. V. 1996 . Evaluating replicability of factors in the revised NEO Personality Inventory: Confirmatory factor analysis versus Procrustes rotation . Journal of Personality and Social Psychology , 70 : 552 – 566 .
- McDonald , R. P. 1989 . An index of goodness-of-fit based on noncentrality . Journal of Classification , 6 : 97 – 103 .
- McDonald , R. P. and Marsh , H. W. 1990 . Choosing a multivariate model: Noncentrality and goodness of fit . Psychological Bulletin , 107 : 247 – 255 .
- Meehl , P. E. 1990 . Appraising and amending theories: The strategy of Lakatosian defense and two principles that warrant it . Psychological Inquiry , 1 : 108 – 141 .
- Mulaik , S. A. 2001 . The curve-fitting problem: An objectivist view . Philosophy of Science , 68 : 218 – 241 .
- Mulaik , S. A. , James , L. R. , Van Alstine , J. , Bennett , N. , Lind , S. and Stilwell , C. D. 1989 . Evaluation of goodness-of-fit indices for structural equation models . Psychological Bulletin , 105 : 430 – 445 .
- Muthén , L. K. and Muthén , B. O. 1998–2011 . Mplus user's guide, , 6th ed. Los Angeles , CA : Author. .
- Myung , I. J. 2000 . The importance of complexity in model selection . Journal of Mathematical Psychology , 44 : 190 – 204 .
- Myung , I. J. and Pitt , M. A. 1998 . “ Issues in selecting mathematical models of cognition. ” . In Localist connectionist approaches to human cognition Edited by: Grainger , J. and Jacobs , A. M. 327 – 355 . Mahwah , NJ : Erlbaum. .
- Nunnally , J. C. and Bernstein , I. H. 1994 . Psychometric theory, , 3rd ed. New York , NY : McGraw-Hill. .
- Pitt , M. A. and Myung , I. J. 2002 . When a good fit can be bad . Trends in Cognitive Sciences , 6 : 421 – 425 .
- Pitt , M. A. , Myung , I. J. and Zhang , S. 2002 . Toward a method of selecting among computational models of cognition . Psychological Review , 109 : 472 – 491 .
- Platt , J. R. 1964 . Strong inference . Science , 146 ( 3642 ) October 16 : 347 – 353 .
- Popper , K. R. 1959 . The logic of scientific discovery. London , , UK : Hutchinson. .
- Preacher , K. J. 2006 . Quantifying parsimony in structural equation modeling . Multivariate Behavioral Research , 41 : 227 – 259 .
- Roberts , S. and Pashler , H. 2000 . How persuasive is a good fit? A comment on theory testing . Psychological Review , 107 : 358 – 367 .
- Savalei , V. 2012 . The relationship between RMSEA and model misspecification in CFA models . Educational and Psychological Measurement , 72 : 910 – 932 .
- Schwarz , G. 1978 . Estimating the dimension of a model . Annals of Statistics , 6 : 461 – 464 .
- Sclove , S. L. 1987 . Application of model-selection criteria to some problems in multivariate analysis . Psychometrika , 52 : 333 – 343 .
- Song , J. and Belin , T. R. 2008 . Choosing an appropriate number of factors in factor analysis with incomplete data . Computational Statistics and Data Analysis , 52 : 3560 – 3569 .
- Steiger , J. H. and Lind , J. C. Statistically based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society . Iowa City , IA . May .
- Thompson , B. 1994 . The pivotal role of replication in psychological research: Empirically evaluating the replicability of sample results . Journal of Personality , 62 : 157 – 176 .
- Thurstone , L. L. 1947 . Multiple-factor analysis: A development and expansion of The Vectors of the Mind. Chicago , IL : The University of Chicago Press. .
- Tucker , L. R. , Koopman , R. F. and Linn , R. L. 1969 . Evaluation of factor analytic research procedures by means of simulated correlation matrices . Psychometrika , 34 : 421 – 459 .
- Wijsman , R. A. 1959 . Applications of a certain representation of the Wishart matrix . Annals of Mathematical Statistics , 30 : 597 – 601 .
- Yuan , K. and Hayashi , K. 2003 . Bootstrap approach to inference and power analysis based on three test statistics for covariance structure models . British Journal of Mathematical and Statistical Psychology , 56 : 93 – 110 .
- Zwick , W. R. and Velicer , W. F. 1986 . Comparison of five rules for determining the number of components to retain . Psychological Bulletin , 99 : 432 – 442 .