Determination of FactorsA with Motor Complications Frequency in People with Early Parkinson's Disease: Bayesian Method for Zero-inflated Poisson Pegression

A. Awaliah, S. Abdullah, Alhadi B.

Research output: Contribution to journalConference articlepeer-review

Abstract

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide that mainly affects motor system. Treatment given to PD patients may have further complications effect such as dyskinesias. People with PD receiving medication often experience complications. It is interest to identify factors associated with the complications. Data on 215people with PD obtained from the Parkinson's Progression Markers Initiative (PPMI) database were analysed. Total scores for the Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS) Part 1, 2, and 3 were used as the explanatory variables. We proposed Zero-Inflated Poisson (ZIP) to model the frequency of motor complications in people with PD. Therefore, the parameters in ZIP regression were estimated using Bayesian approach. Sampling from the posterior distribution of the parameters is conducted using Monte Carlo Markov Chain-Gibbs Sampling (MCMC-GS). The result shows that total score of MDS-UPDRS Part 1 and 2 are negatively associated with people for no need medication while the opposite is observed for total score of Part 3. Furthermore, in the second stage of the model, total score of Part 3is negatively associated with frequency of complications, while the opposite trend is observed for total score of Part 1 and 2.

Original languageEnglish
Article number012021
JournalJournal of Physics: Conference Series
Volume1108
Issue number1
DOIs
Publication statusPublished - 4 Dec 2018
Event2nd Mathematics, Informatics, Science and Education International Conference, MISEIC 2018 - Surabaya, Indonesia
Duration: 21 Jul 2018 → …

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