Suppose that a heterogeneous group of individuals is followed over time and that each
individual can be in state 0 or state 1 at each time point. The sequence of states is assumed …

Markov chain models are frequently used for studying event histories that include transitions
between several states. An empirical transition matrix for nonhomogeneous Markov chains …

Abstract SUMMARY A stochastic model is proposed for the study of the influence of time-
dependent covariates on the marginal distribution of the binary response in serially …

During the recent past, there has been a renewed interest in Markov chain for its attractive
properties for analyzing real life data emerging from time series or longitudinal data in …

In this paper, situations in which individuals move through a finite set of states according to a
continuous-time Markov process are considered. Only aggregate data are available: these …

Estimation in Markov chains from aggregate data is discussed. The information about
different aspects of a chain, such as individual transition probabilities, the equilibrium …

Many chronic diseases are measured by repeated binary data where the scientific interest is
on the transition process between two states of disease activity. Examples include …

Consider a population of n individuals that move independently among a finite set {1, 2,……,
k} of states in a sequence of trials. t= 0. 1, 2,…, m. each according to a Markov chain with …

The paper reviews different techniques for examining sequential dependencies in a series
of observations each of which can have c possible outcomes. The relationship between the …

A study of the relapse and survival times for 300 breast cancer patients submitted to post‐
surgical treatments is presented. After surgery, these patients were given three treatments …