References

 

(To request a Muthén paper, please email bmuthen@ucla.edu and refer to the number in parenthesis.)

 

Analysis With Continuous Outcomes

 

EFA

 

Bartholomew, D.J. (1987).  Latent variable models and factor analysis. New York: Oxford University Press.

 

Fabrigar, L.R., Wegener, D.T., MacCallum, R.C. & Strahan, E.J.  (1999).  Evaluating the use of exploratory factor analysis in psychological research.  Psychological Methods , 4, 272-299.

 

Gorsuch, R.L. (1983).  Factor analysis. 2nd edition. Hillsdale, N.J.:  Lawrence Erlbaum.

 

Harman, H.H. (1976).  Modern factor analysis. 3rd edition.  Chicago:  The University of Chicago Press.

 

Holzinger, K. J. & Swineford, F. (1939).  A study in factor analysis: The stability of a bi-factor solution.  Supplementary Educational Monographs.  Chicago, Ill.: The University of Chicago.

 

Joreskog, K.G. (1977).  Factor analysis by least-squares and maximum-likelihood methods.  In Statistical methods for digital computers, K. Enslein, A. Ralston, and H.S. Wilf (Eds.). New York: John Wiley & Sons, pp. 125-153.

 

Joreskog, K.G. (1979).  Author's addendum.  In Advances in factor analysis and structural equation models, J. Magidson (Ed.). Cambridge, Massachusetts: Abt Books, pp. 40-43.

 

Kim, J.O. & Mueller, C.W. (1978).  An introduction to factor analysis: what it is and how to do it.  Sage University Paper series on Quantitative Applications in the Social Sciences, No 07-013.  Beverly Hills, CA: Sage.

 

Millsap, R.E. (2001).  When trivial constraints are not trivial: the choice of uniqueness constraints in confirmatory factor analysis.  Structural Equation Modeling, 8, 1-17.

 

Mulaik, S. (1972).  The foundations of factor analysis.  McGraw-Hill.

 

Schmid, J. & Leiman, J.M. (1957).  The development of hierarchical factor solutions.  Psychometrika, 22, 53-61.

Spearman, C. (1927).  The abilities of man.  New York: Macmillan.

 

Thurstone, L.L. (1947).  Multiple factor analysis. Chicago: University of Chicago Press.

 

Tucker, L.R. (1971).  Relations of factor score estimates to their use. Psychometrika, 36, 427-436.

CFA

 

Joreskog, K.G. (1969).  A general approach to confirmatory maximum likelihood factor analysis.  Psychometrika, 34.

 

Joreskog, K.G. (1971).  Simultaneous factor analysis in several populations. Psychometrika, 36, 409-426.

 

Lawley, D.N. & Maxwell, A.E. (1971).  Factor analysis as a statistical method.  London: Butterworths.

 

Long, S. (1983).  Confirmatory factor analysis.  Sage University Paper series on Quantitative Applications in the Social Sciences, No 33.  Beverly Hills, CA: Sage.

 

Meredith, W. (1964).  Notes on factorial invariance. Psychometrika, 29, 177-185.

Meredith, W. (1993).  Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525-543.

 

Muthen, B.  (1989b). Factor structure in groups selected on observed scores.  British Journal of Mathematical and Statistical Psychology, 42, 81-90. (#23)

 

Muthen, B.  (1989c).  Multiple-group structural modeling with non-normal continuous variables. British Journal of Mathematical and Statistical Psychology, 42, 55-62. (#26)

 

Muthén, B., & 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.

 

Muthén, B., & 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.

 

Sorbom, D. (1974).  A general method for studying differences in factor means and factor structure between groups.  British Journal of Mathematical and Statistical Psychology, 27, 229-239.

 

 

 

 

MIMIC

 

Hauser, R.M. & Goldberger, A.S. (1971).  The treatment of unobservable variables in path analysis. In H. Costner (Ed.),  Sociological Methodology (pp. 81-117).  American Sociological Association: Washington, D.C.

 

Joreskog, K.G., & Goldberger, A.S. (1975).  Estimation of a model with multiple indicators and multiple causes of a single latent variable. Journal of the American Statistical Association, 70, 631-639.

Muthen, B.  (1989a).  Latent variable modeling in heterogeneous populations. Psychometrika, 54, 557-585. (#24)

 

SEM

 

Amemiya, T. (1985).  Advanced econometrics. Cambridge, Mass.: Harvard University Press.

Bollen, K.A. (1989).  Structural equations with latent variables.  New York: John Wiley.

 

Browne, M.W. & Arminger, G. (1995).  Specification and estimation of mean- and covariance-structure models. In G. Arminger, C.C. Clogg & M.E. Sobel (Eds.), Handbook of statistical modeling for the social and behavioral sciences (pp. 311-359).  New York: Plenum Press.

 

Browne, M.W., & Cudeck, R.  (1993).  Alternative ways of assessing model fit.  In K. Bollen & K. Long (Eds.), Testing structural equation models (pp. 136-162).  Newbury Park:  Sage.

 

Hu, L. & Bentler, P. M. (1998).  Fit indices in covariance structure analysis:  Sensitivity to underparameterized model misspecification.  Psychological Methods, 3, 424-453.

 

Hu, L. & Bentler, P. M. (1999).  Cutoff criterion for fit indices in covariance structure analysis: conventional criteria versus new alternatives.  Structural Equation Modeling, 6, 1-55.

 

Joreskog, K.G. (1973).  A general method for estimating as linear structural equation system.  In Structural Equation Models in the Social Sciences, A.S. Goldberger and O.D. Duncan Eds.).  New York: Seminar Press, pp. 85-112.

 

Joreskog, K.G., & Sorbom, D. (1979).  Advances in factor analysis and structural equation models.  Cambridge, MA: Abt Books.

 

Kaplan, D. (2000).  Structural equation modeling.  Foundations and extensions. Thousand Oakes, CA:  Sage Publications.

 

Kline, R.B. (1998).  Principles and practice of structural equation

modeling.   New York, NY:  Guilford Press

 

MacCallum, R. C. & Austin, J. T. (2000).  Applications of structural equation modeling in psychological research.  Annual Review of Psychology, 51, 201-226.

 

MacKinnon, D.P., Lockwood, C.M., Hoffman, J.M., West, S.G. & Sheets, V. (2002).  A comparison of methods to test mediation and other intervening variable effects.  Psychological Methods, 7, 83-104.

 

Raykov, T. & Marcoulides, G. A. (2000).  A first course in structural

equation modeling. Mahwah, NJ: Erlbaum.

 

Satorra, A. (2000).  Scaled and adjusted restricted tests in multi-sample analysis of moment structures. In Heijmans, R.D.H., Pollock, D.S.G. & Satorra, A. (eds.),  Innovations in Multivariate Statistical Analysis. A Festschrift for Heinz Neudecker (pp.233-247). London: Kluwer Academic Publishers.

 

Satorra, A. & Bentler, P.M. (1999).  A scaled difference chi-square test statistic for moment structure analysis. Technical report, University of California, Los Angeles.

 

Shrout, P.E. & Bolger, N. (2002).  Mediation in experimental and nonexperimental studies: New procedures and recommendations.  Psychological Methods, 7, 422-445.

 

Sorbom, D. (1989).  Model modification.  Psychometrika, 54, 371-384.

 

Steiger, J.H. & Lind, J.M. (1980).  Statistically based tests for the number of common factors.  Paper presented at the annual meeting of the Psychometric Society, Iowa City, IA.

 

Wheaton, B., Muthen, B., Alwin, D., & Summers, G. (1977).  Assessing reliability and stability in panel models.  In D.R. Heise (Ed.), Sociological Methodology 1977 (pp. 84-136).  San Francisco: Jossey-Bass.  (#1)

 

Yu, C.-Y. & Muthén, B. (2002).  Evaluation of model fit indices for latent variable models with categorical and continuous outcomes.  Technical report.

 

General

 

Lord, F.M. & Novick, M.R. (1968).  Statistical theories of mental test scores.  Reading, Mass.: Addison-Wesley Publishing Co.

 

Muthén, L.K. and Muthén, B.O. (2002).  How to use a Monte Carlo study to decide on sample size and determine power.  Structural Equation Modeling, 4, 599-620. (#97)

 

 

http://www.gsu.edu/~mkteer/bookfaq.html http://gsm.uci.edu/~joelwest/SEM/SEMBooks.html

http://www2.chass.ncsu.edu/garson/pa765/structur.htm is a fairly complete

(15 pages) general overview of SEM.

SEMNET@BAMA.UA.EDU