Estimation of the transition matrix of a discrete-time Markov chain.

Abstract:

:Discrete-time Markov chains have been successfully used to investigate treatment programs and health care protocols for chronic diseases. In these situations, the transition matrix, which describes the natural progression of the disease, is often estimated from a cohort observed at common intervals. Estimation of the matrix, however, is often complicated by the complex relationship among transition probabilities. This paper summarizes methods to obtain the maximum likelihood estimate of the transition matrix when the cycle length of the model coincides with the observation interval, the cycle length does not coincide with the observation interval, and when the observation intervals are unequal in length. In addition, the bootstrap is discussed as a method to assess the uncertainty of the maximum likelihood estimate and to construct confidence intervals for functions of the transition matrix such as expected survival.

journal_name

Health Econ

journal_title

Health economics

authors

Craig BA,Sendi PP

doi

10.1002/hec.654

keywords:

subject

Has Abstract

pub_date

2002-01-01 00:00:00

pages

33-42

issue

1

eissn

1057-9230

issn

1099-1050

pii

10.1002/hec.654

journal_volume

11

pub_type

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