Finite mixture models with applications to demography.

Thesis Report.

ABSTRACT: This thesis intends to be methodological. We propose a general framework to incorporate unobserved heterogeneity in the statistical analysis that can be easily applied in demographic research. Before introducing the finite mixture framework, we revise the maximum likelihood estimation in the homogeneous case. Then, we extend the heterogeneous case, assuming and unknown number of components in the finite mixture for independent observations. Furthermore, we extend this framework to accommodate dependent observations following a Markov chain (finite mixture of Markov chains). Finally, a model defined for static (cross-sectional) and dynamic (longitudinal) variables is proposed. These models were implemented in MATALAB5.3. The models defined are illustrated, using the data from Brazil Demographic and Health Survey (BDHS) 1996, focusing on women's attitudes towards family planning and contraceptive use dynamics. Individual respondents (women) were segmented based on different attitudes reported towards family planning and contraceptive use dynamics. Key words : Finite mixture models, Latent class analysis, Segmentation techniques, Markov models, Contraceptive use dynamics

Eng.