Conducting confirmatory latent class analysis using Mplus

Structural Equation Modeling

Volumn 18, Issue 1, 2011, Pages 132-151

  Finch, W Holmes ^a   Bronk, Kendall Cotton ^a  

^a BALL STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 78651337307     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1080/10705511.2011.532732     Document Type: Article

References (21)

1. Benson, P. L. (2006). All kids are our kids: What communities must do to raise caring and responsible children and adolescents (2nd ed.). San Francisco, CA: Jossey Bass.
2. Bundick, M., Andrews, M., Jones, A., Mariano, J. M., Bronk, K. C., & Damon, W. (2006). Revised youth purpose survey. Unpublished instrument, Stanford Center on Adolescence, Stanford, CA.
3. Croon, M. A. (1990). Latent class analysis with ordered latent classes. British Journal of Mathematical and Statistical Psychology, 43, 171-192.
4. Damon, W. (2009). The path to purpose: How young people find their calling in life. New York: Free Press.
5. Damon, W., Menon, J., & Bronk, K. C. (2003). The developmentof purposeduring adolescence. Applied Developmental Science, 7(3), 119-128.
6. De Vogler, K. L., & Ebersole, P. (1980). Categorization of college students' meaning in life. Psychological Reports, 46,387-390.
7. De Vogler, K. L., & Ebersole, P. (1981). Adults' meaning in life. Psychological Reports, 49, 87-90.
8. De Vogler, K. L., & Ebersole, P. (1983). Young adolescents' meaning in life. Psychological Reports, 52, 427-431.
9. Fienberg, S. E. (1979). The use of chi-squared statistics for categorical data problems. Journal of the Royal Statistical Society, Series B, 41, 425-439.
10. Goodman, L. A. (2002). Latent class analysis: The empirical study of latent types, latent variables, and latent structures. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 3-55). Cambridge, UK: Cambridge University Press.
11. Henson, J. M., Reise, S. P., & Kim, K. H. (2007). Detecting mixtures from structural model differences using latent variable mixture modeling: A comparison of relative model fit statistics. Structural Equation Modeling, 14, 202-226.
12. Hoijtink, H. (2001). Confirmatory latent class analysis: Model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Statistics, 36, 563-588.
13. Laudy, O., Boom, J., & Hoijtink, H. (2005). Bayesian computational methods for inequality constrained latent class analysis. In L. A. van der Ark, M. A. Croon, & K. Sijtsma (Eds.), New developments in categorical data analysis for the social and behavioral sciences (pp. 63-82). Mahwah, NJ: Lawrence Erlbaum Associates.
14. Lo, Y., Mendell, N., & Rubin, D. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767-778.
15. McCutcheon, A. L. (2002). Basic concepts and procedures in single-and multiple-group latent class analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 57-88). Cambridge, UK: Cambridge University Press.
16. McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley.
17. Muthén, B. O. (2001). Latent variable mixture modeling. In G. A. Marcoulides & R. E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 1-34). Mahwah, NJ: Lawrence Erlbaum Associates.
18. Muthén, L. K., & Muthén, B. O. (2008). Mplus user's guide (5th ed.). Los Angeles: Muthén & Muthén.
19. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535-569.
20. Rudas, T. (1986). A Monte Carlo comparison of the small sample behavior of the Pearson, the likelihood ratio and the Cressie-Read statistics. Journal of Statistical Computation and Simulation, 24, 107-120.
21. Showalter, S. M., & Wagener, L. M. (2000). Adolescents' meaning in life: A replication of De Vogler and Ebersole (1983). Psychological Reports, 87, 115-126.