On the estimation of interval censored destructive negative binomial cure model.

ABSTRACT: In this article, a competitive risk survival model is considered in which the initial number of risks, assumed to follow a negative binomial distribution, is subject to a destructive mechanism. Assuming the population of interest to have a cure component, the form of the data as interval-censored, and considering both the number of initial risks and risks remaining active after destruction to be missing data, we develop two distinct estimation algorithms for this model. Making use of the conditional distributions of the missing data, we develop an expectation maximization (EM) algorithm, in which the conditional expected complete log-likelihood function is decomposed into simpler functions which are then maximized independently. A variation of the EM algorithm, called the stochastic EM (SE

SUBMITTER: Treszoks J 

PROVIDER: S-EPMC11099949 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature