Aitkin, M., Anderson, D., & Hinde, J. (1981). Statistical modeling of data on teaching styles (with discussion). Journal of the Royal Statistical Society A, 144, 419-461.
2.
Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In N. Petrov & F. Csaki (Eds.), 2nd International Symposium on Information Theory(pp. 267-281). Budapest: Akademiai Kiado.
3.
Clogg, C. C. (1995). Latent class models. In G. Arminger, C. C. Clogg, & M. E. Sobel (Eds.), Handbook of statistical modeling for the social sciences(pp. 311-360). New York: Plenum.
4.
Cressie, N., & Read, T. R. C. (1984). Multinomial goodness-of-fit tests. Journal of the Royal Statistical Society B, 46, 440-464.
5.
Dayton, C. M. (1999). Latent class scaling analysis (Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-126). Thousand Oaks, CA: Sage.
6.
Ihaka, R.,& Gentleman, R. (1996). R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5, 299-314.
7.
Langeheine, R., Pannekoek, J., & van de Pol, F. (1996). Bootstrapping goodness-of-fit measures in categorical data analysis. Sociological Methods & Research, 24, 492-516.
8.
Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. Mew York: Houghton-Mifflin.
9.
McCutcheon A. C. (1987). Latent class analysis. Beverly Hills, CA: Sage.
10.
McLachlan, G. J., & Basford, K. E. (1988). Mixture models. New York: Marcel Dekker.
11.
Read, T. R. C.,& Cressie, N. A. C. (1988). Goodnessoffit statistics for discrete multivariate data. New York: Springer-Verlag.
12.
Rindskopf, R., & Rindskopf, W. (1986). The value of latent class analysis in medical diagnosis. Statistics in Medicine, 5, 21-27.
13.
Rost, J., & Langeheine, R. (Eds.). (1997). Applications of latent trait and latent class models in the social sciences. Muenster, Germany: Waxmann.
14.
Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
