Parameter Estimation in Logistic Regression for Transition, Reverse Transition and Repeated Transition from Repeated Outcomes

• 作者: Laurent Briollais M. Ataharul Islam Rafiqul I. Chowdhury Shahariar Huda
• 来源期刊: 应用数学(英文)
• 学科: 医学
• 关键词: COMPUTER PROGRAM MARKOV Model TRANSITION REVERSE TRANSITION Repeated TRANSITION
• 年，卷（期）: 2012,（11）
• 页码范围: 1739-1749
• 页数: 11页
• 分类号: R73

摘要

Covariate dependent Markov models dealing with estimation of transition probabilities for higher orders appear to be restricted because of over-parameterization. An improvement of the previous methods for handling runs of events by expressing the conditional probabilities in terms of the transition probabilities generated from Markovian assumptions was proposed using Chapman-Kolmogorov equations. Parameter estimation of that model needs extensive pre-processing and computations to prepare data before using available statistical softwares. A computer program developed using SAS/IML to estimate parameters of the model are demonstrated, with application to Health and Retirement Survey (HRS) data from USA.