Proportional Odds Model for Health States Analysis
Keywords:health status, disability, repeated responses, Markov Chain Model, Proportional Odds Model
Employeesâ€™ health status is one of the key issues that should be considered in ensuring the economic growth of a country. Information on employeesâ€™ health status is useful in social and economic studies, especially in issues related to work-related disabilities and deaths. The estimation of disability probability involves a challenging method as a disabled employee may move from one state to another (from temporary to permanent, or vice versa), or from one event to another (from disabled to active, or to death), implying that repeated responses may be obtained at different time points in the relevant longitudinal studies. Markov Chain Model can be used to analyze repeated measurements, or ordinal responses in a longitudinal data, and to compare between one health states to another. The main objective of this study is to estimate the Markov transition probabilities between health states using the Proportional Odds Model (POM) based on the dataset obtained from Social Security Organization, Malaysia (SOCSO). The results show that female employees in age group 55-59 have the highest probability of remaining in active state (A), while male employees in age group 15-19 have the lowest probability of remaining in active state (A), or have the highest risk of transitioning from healthy state to disability or death states.
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