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PubMed · 10682528

[Markov process method in analyzing longitudinal quality of life data].

C Wan·J Fang·W Zhou
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Abstract

OBJECTIVE: To present a method to analyze longitudinal quality of life data and discuss some relevant questions. METHOD: Based on the theories of Markov process, the Markov method was presented and used to analyze the change of quality of life status for 212 cases being detoxificated drug addicts and their influence factors. RESULTS: The intensity coefficients of status transient for 1-->2 and 2-->3 for occupation were 0.7912 and 0.6797 respectively; the coefficients for status 1-->2 for the detoxification time was 0.5663 and that for 2-->3 for the detoxification method was 0.2765. CONCLUSIONS: The Markov method is good to analyze longitudinal quality of life data for it can analyze both the transient probabilities between any two status of quality of life and their influence factors. The results showed that the occupation of drug addicts, the detoxification time and method can affect the change of quality of life.

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HumansLongitudinal StudiesMarkov ChainsQuality of LifeSubstance Withdrawal SyndromeSubstance-Related DisordersEnglish AbstractJournal ArticleResearch Support, Non-U.S. Gov't

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C Wan, J Fang, W Zhou. 1999. [Markov process method in analyzing longitudinal quality of life data].. https://pubmed.ncbi.nlm.nih.gov/10682528/

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