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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/151245


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/151245


    Title: Determination of correlations in multivariate count data with informative observation times
    Authors: 黃佳慧
    Huang, Chia-Hui
    Contributors: 統計系
    Keywords: Bayesian analysis;covariance matrix;multivariate count data;multivariate frailty model;observation process
    Date: 2024-02
    Issue Date: 2024-05-24 11:00:42 (UTC+8)
    Abstract: We consider there are various types of recurrent events and the total number of occurrences are collected at the random observation times. It has concerned that the observation process may not be independent to the multivariate event processes, hence the total counts and observation times may be correlated and the dependence may exist among different types of the event processes as well. Many methods have developed nonparametric models to accommodate such unknown structures; however, it is difficult to assess and directly quantify their correlation relationships. A multivariate frailty model is proposed to this study, in which the event and observation processes are linked by frailty variables whose joint distribution can be implicitly specified through the multivariate normal distribution with some unknown covariance matrix. The Bayesian inference method is conducted to obtain the estimates of the regression coefficients and correlation parameters. We use a form of trigonometric functions to represent the covariance matrix, so that it meets the positive-definiteness condition efficiently during the estimation schemes. The simulation studies demonstrate the utility of the proposed models. We apply the model to a skin cancer prevention study, and aim to determine the covariate and association effects. We found treatment is significant in determining the duration of examination times; prior-counts, age and gender are significant variables on the occurrence rates of tumor counts. Using the covariance matrix to access the underlying dependent structure, the mutual correlations among them are all positive, and the basal cell counts are more related to the examination times.
    Relation: Statistical Methods in Medical Research, Vol.33, No.2, pp.273-294
    Data Type: article
    DOI 連結: https://doi.org/10.1177/09622802231224632
    DOI: 10.1177/09622802231224632
    Appears in Collections:[統計學系] 期刊論文

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