A theoretical foundation for state-transition cohort models in health decision analysis.

ABSTRACT: Following its introduction over three decades ago, the cohort model has been used extensively to model population trajectories over time in decision-analytic modeling studies. However, the stochastic process underlying cohort models has not been properly described. In this study, we explicate the stochastic process underlying a cohort model, by carefully formulating the dynamics of populations across health states and assigning probability rules on these dynamics. From this formulation, we explicate a mathematical representation of the system, which is given by the master equation. We solve the master equation by using the probability generation function method to obtain the explicit form of the probability of observing a particular realization of the system at an arbitrary time. The resul

SUBMITTER: Iskandar R 

PROVIDER: S-EPMC6289421 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature