Multistate Analysis of Life Histories with R (Use R!) - Tapa blanda

“The book is largely built around a description of population change as a set of life histories, viewed as the realization of stochastic processes. ... This book is a very nice addition to the many other important methodological contributions made by Frans Willekens and I recommend that it be read by all demographers ... .” (David A. Swanson, Canadian Studies in Population, Vol. 42 (3-4), 2015)

“This book is about pragmatic analysis of life histories using a selection of packages for statistical programming language R. ... I recommend the book for everyone interested in pragmatic analyses of life histories with R. ... successfully provides a well-justified selection of useful methods with (now) well-documented tools for pragmatic analyses of multistate life histories.” (Reijo Sund, International Statistical Review, Vol. 83 (2), 2015)

This book provides an introduction to multistate event history analysis. It is an extension of survival analysis, in which a single terminal event (endpoint) is considered and the time-to-event is studied. Multistate models focus on life histories or trajectories, conceptualized as sequences of states and sequences of transitions between states. Life histories are modeled as realizations of continuous-time Markov processes. The model parameters, transition rates, are estimated from data on event counts and populations at risk, using the statistical theory of counting processes.

The Comprehensive R Network Archive (CRAN) includes several packages for multistate modeling. This book is about Biograph. The package is designed to (a) enhance exploratory analysis of life histories and (b) make multistate modeling accessible. The package incorporates utilities that connect to several packages for multistate modeling, including survival, eha, Epi, mvna<, etm, mstate, msm, and TraMineR for sequence analysis. The book is a ‘hands-on’ presentation of Biograph and the packages listed. It is written from the perspective of the user. To help the user master the techniques and the software, a single data set is used to illustrate the methods and software. It is the subsample of the German Life History Survey, which was also used by Blossfeld and Rohwer in their popular textbook on event history modeling. Another