Open AccessEstimating Markov Transition Probabilities Between Health States in the Social Security Malaysia (SOCSO) Dataset
Author(s) -
Shamshimah Samsuddin,
Noriszura Ismail
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k1043.09811s219
Subject(s) - social security , odds , affect (linguistics) , markov chain , markov model , transition (genetics) , work (physics) , demographic economics , psychology , gerontology , actuarial science , demography , econometrics , statistics , logistic regression , sociology , medicine , economics , mathematics , engineering , biochemistry , chemistry , gene , mechanical engineering , communication , market economy
Occupational injury represents a considerable part of injury burden to the society as it may affect workers in their most productive years. The objective of this paper is to estimate the Markov transition probabilities of a worker’s health states over time using the Counting Method (CM) and the Proportional Odds Model (POM), focusing on disability among the Social Security Organization (SOCSO) contributors in Malaysia. Four health states namely active/work (A), temporary disability (T), permanent disability (P) and death (D) are considered, where the transition probabilities are estimated at yearly intervals based on age, gender, year and disability category.