Non-homogeneous Markov process models for life history data are studied. We review
Aalen & Johansen's (1978) methodology for estimating transition probabilities in such …

Non-parametric estimation of the transition probabilities in multi-state models is considered
for non-Markov processes. Firstly, a generalization of the estimator of Pepe et …

Nonparametric likelihood methods are developed for the analysis of partially censored data
arising from a multistate stochastic process. It is assumed that the underlying process follows …

The nonparametric estimation of the cumulative transition intensity functions in a threestate
time-nonhomogeneous Markov process with irreversible transitions, an 'illness-death'model …

Given aggregated longitudinal data generated by a Markov chain, which may be
nonhomogeneous, the problem considered is that of modelling, estimating and interpolating …

Estimation in a three‐state Markov process with irreversible transitions in the presence of
interval‐censored data is considered. A nonparametric maximum likelihood procedure for …

Aalen and Johansen have developed a powerful methodology of nonparametric inference
on transition probabilities of discrete state Markov processes based on Aalen's framework …

The product limit method of Kaplan and Meier for estimating survival functions and the
logrank test of Mantel are widely employed for analysis of longitudinal medical data …

Abstract The Aalen-Johansen estimator generalizes the Kaplan-Meier estimator for
independently left-truncated and right-censored survival data to estimate the transition …

Multi‐state models are often used for modeling complex event history data. In these models
the estimation of the transition probabilities is of particular interest, since they allow for long …