%0 Journal Article
%T Parameter Estimation in Logistic Regression for Transition, Reverse Transition and Repeated Transition from Repeated Outcomes
%A Rafiqul I. Chowdhury
%A M. Ataharul Islam
%A Shahariar Huda
%A Laurent Briollais
%J Applied Mathematics
%P 1739-1749
%@ 2152-7393
%D 2012
%I Scientific Research Publishing
%R 10.4236/am.2012.331240
%X 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.
%K Computer Program
%K Markov Model
%K Transition
%K Reverse Transition
%K Repeated Transition
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=24752