| Coordinator | Mauricio Garnier-Villarreal (VU) |
| Mauricio Garnier-Villarreal | |
| Date | November 2027 Date(s) to be decided |
| Venue | Vrije Universiteit Amsterdam (VU) |
| Mandatory/Elective | Elective |
| ECTS | 2 |
| Registration | secretariaat@iops.nl |
| Fee | IOPS members: free Affiliated members: To be announced |
| Abstract | We work on categorical latent variables that identify typologies of subjects, these are “Finite mixture models”. In direct applications, one assumes that the overall population heterogeneity with respect to a set of manifest variables is due to the existence of two or more distinct homogeneous subgroups (latent classes) of individuals. This seminar will introduce participants to the prevailing “best practices” for direct applications of finite mixture modeling to cross-sectional data (Latent Class Analysis, and Latent Profile Analysis), in terms of model assumptions, specification, estimation, evaluation, selection, and interpretation. Models that allow for the inclusion of correlates and predictors of latent class membership as well as distal outcomes of latent class membership will be presented. The course will end by presenting longitudinal extensions of mixture models (Hidden Markov Models). These models estimate the probability to stay or switch classes over time, allowing us to study the process of change of meaningful typologies. |
| Examination | To be announced |
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