TPmsm: Estimation of the Transition Probabilities in 3-State Models

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Authors Artur Ara, Javier Roca-Pardi
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper Abstract One major goal in clinical applications of multi-state models is the estimation of transition probabilities. The usual nonparametric estimator of the transition matrix for nonhomogeneous Markov processes is the Aalen-Johansen estimator (Aalen and Johansen 1978). However, two problems may arise from using this estimator: rst, its standard error may be large in heavy censored scenarios; second, the estimator may be inconsistent if the process is non-Markovian. The development of the R package TPmsm has been motivated by several recent contributions that account for these estimation problems. Estimation and statistical inference for transition probabilities can be performed using TPmsm. The TPmsm package provides seven dierent approaches to three-state illnessdeath modeling. In two of these approaches the transition probabilities are estimated conditionally on current or past covariate measures. Two real data examples are included for illustration of software usage.
Date of publication 1978
Code Programming Language R
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