Finite mixture modeling with mixture outcomes using the EM algorithm

Biometrics

Volumn 55, Issue 2, 1999, Pages 463-469

  Muthén, Bengt ^a   Shedden, Kerby ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Growth modeling; Latent class analysis; Latent variables; Maximum likelihood; Trajectory classes

Indexed keywords

MAXIMUM LIKELIHOOD ESTIMATION;

EM ALGORITHMS; FINITE MIXTURE MODELING; GROWTH MODELS; LATENT CLASS; LATENT CLASS ANALYSIS; LATENT VARIABLE; MA XIMUM LIKELIHOODS; MAXIMUM-LIKELIHOOD; MIXTURE COMPONENTS; TRAJECTORY CLASS;

TRAJECTORIES;

ALCOHOL CONSUMPTION; ALGORITHM; ARTICLE; GROWTH CURVE; MAXIMUM LIKELIHOOD METHOD; STATISTICAL ANALYSIS; STATISTICAL MODEL;

EID: 0032969449     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.1999.00463.x     Document Type: Article

References (8)

1. Clogg, C. C. (1995). Latent class models. In Handbook of Statistical Modeling for the Social and Behavioral Sciences, G. Arminger, C. C. Clogg, and M. E. Sobel (eds), 311-359. New York: Plenum.
2. Follman, D. A. and Lambert, D. (1989). Generalizing logistic regression by nonparametric mixing. Journal of the American Statistical Association 84, 294-300.
3. Follman, D. A. and Lambert, D. (1991). Identifiability of finite mixtures of logistic regression models. Journal of Statistical Planning and Inference 27, 375-381.
4. Lawley, D. N. and Maxwell, A. E. (1971). Factor Analysis as a Statistical Method. London: Butterworths.
5. McLachlan, G. J. and Krishnan, T. (1997). The EM Algorithm and Extensions. New York: John Wiley and Sons.
6. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics 6, 461-464.
7. Titterington, D. M., Smith, A. F. M., and Makov, U. E. (1985). Statistical Analysis of Finite Mixture Distributions. Chichester, U.K.: John Wiley and Sons.
8. Verbeke, G. and Lesaffre, E. (1996). A linear mixed-effects model with heterogeneity in the random-effects population. Journal of the American Statistical Association 91, 217-221.