Markov Cohort State-Transition Model: A Multinomial Distribution Representation

Rowan Iskandar; Cassandra Berns

doi:10.1177/0272989X221112420

Markov Cohort State-Transition Model: A Multinomial Distribution Representation

Med Decis Making. 2023 Jan;43(1):139-142. doi: 10.1177/0272989X221112420. Epub 2022 Jul 15.

Authors

Rowan Iskandar^{1

2

3}, Cassandra Berns^{1

2}

Affiliations

¹ Center of Excellence in Decision-Analytic Modeling and Health Economics Research, sitem-insel, Bern, Switzerland.
² Brown University, Providence, RI, USA.
³ Institute of Social and Preventive Medicine, University of Bern, Switzerland.

PMID: 35838344
DOI: 10.1177/0272989X221112420

Abstract

A Markov model simulates the average experience of a cohort of patients.Monte Carlo simulation, the standard approach for estimating the variance, is computationally expensive.A multinomial distribution provides an exact representation of a Markov model.Using the known formulas of a multinomial distribution, the mean and variance of a Markov model can be readily calculated.

Keywords: cohort model; cost-effectiveness analysis; decision-analytic model; markov model; state-transition model.

MeSH terms

Humans
Markov Chains*
Monte Carlo Method