UNIGE document Doctoral Thesis
previous document  unige:74459  next document
add to browser collection

Markovian modelling of life course data

Defense Thèse de doctorat : Univ. Genève, 2015 - SdS 13 - 2015/06/10
Abstract Markovian models describe how the current measurement depends on the previously observed measures and on factors both observed and unobservable in the data. The dissertation underlines the several features that make Markovian modelling an interesting approach for life course studies focusing in particular on latent-based Markov models. In such an approach the dynamics of a characteristic of interest is explained by the evolution in time of a latent variable. This approach is particularly interesting in life course studies since many factors that are unobserved or difficult-to-observe in the data may influence a life history and can change over time. The dissertation discusses on a general framework for modelling longitudinal continuous data by the means of a latent based Markov model. The model incorporates a latent Markov process that governs the switching among regimes of change, the dependence between successive observations with an autoregressive component and the effect of the time-varying covariates. Empirical applications in population studies from three different sources are discussed.
Keywords Life course dataApplied statisticsLongitudinal dataMarkov modelsHidden Markov ModelsSocial statistics.
URN: urn:nbn:ch:unige-744593
Full text
Thesis (1.3 MB) - document accessible for UNIGE members only Limited access to UNIGE
(ISO format)
BOLANO, Danilo. Markovian modelling of life course data. Université de Genève. Thèse, 2015. https://archive-ouverte.unige.ch/unige:74459

238 hits



Deposited on : 2015-08-03

Export document
Format :
Citation style :