Iskandar, Rowan; Berns, Cassandra (2023). Markov Cohort State-Transition Model: A Multinomial Distribution Representation. Medical decision making, 43(1), pp. 139-142. Sage Publications 10.1177/0272989X221112420
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HIGHLIGHTS
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.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Faculty Institutions > sitem Center for Translational Medicine and Biomedical Entrepreneurship 04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM) |
UniBE Contributor: |
Iskandar, Rowan |
Subjects: |
600 Technology > 610 Medicine & health 300 Social sciences, sociology & anthropology > 360 Social problems & social services |
ISSN: |
0272-989X |
Publisher: |
Sage Publications |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
19 Jul 2022 12:24 |
Last Modified: |
09 Apr 2024 09:45 |
Publisher DOI: |
10.1177/0272989X221112420 |
PubMed ID: |
35838344 |
Uncontrolled Keywords: |
cohort model cost-effectiveness analysis decision-analytic model markov model state-transition model |
BORIS DOI: |
10.48350/171345 |
URI: |
https://boris.unibe.ch/id/eprint/171345 |
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