Seminario IESTA (SIESTA)

El miércoles 12 de mayo a las 14 horas tendrá lugar un nuevo Seminario del IESTA (SIESTA) titulado Continuous-time multi-state models.

La actividad estará a cargo de Ardo Van Den Hout (Associate Professor in Statistics-Department of Statistical Science-University College London-United Kingdom).

ID: 895 1462 8879
Contraseña: k!7yDCtCM4

Resumen

Multi-state models are routinely used in research where change of status over time is of interest. In epidemiology and medical statistics, for example, the models are used to describe health-related processes over time, where status is defined by a disease or a condition. In social statistics and in demography, the models are used to study processes such as region of residence, work history, or marital status.

A Markov model is an example of a multi-state model. Markov models are often used in economic evaluation of healthcare interventions. Markov models are also a used to describe the stochastic nature of economic and financial variables in times series.

Part of the talk will be an introduction to continuous-time multi-state survival models. I will discuss longitudinal data requirements, the link with stochastic processes, and maximum likelihood inference. An important distinction is whether or not exact times are observed for transitions between the states. In many applications, we do not have exact times and it is important to take this into account in the statistical analysis.

Two applications will be discussed. (i) For an illness-death process, I will illustrate estimating time spent in states. In ageing research, this can be used to distinguish total residual life expectancies from healthy residual life expectancy. (ii) For employment history, I will discuss a model for change of job using longitudinal data from the German Life History Study.

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