利用相关复合泊松虚弱模型分析肾脏感染数据

Q4 Mathematics

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI:10.3233/mas-231452

David D. Hanagal

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引用次数: 0

摘要

共享虚弱模型尽管有其局限性，但仍被使用。为了克服其缺点，可以使用相关虚弱模型。本文介绍了具有两种不同基线分布（即广义 log logistic 和广义 Weibull）的相关复合泊松虚弱模型。我们介绍了使用马尔可夫链蒙特卡罗（MCMC）技术的贝叶斯估计程序，以估计这些模型所涉及的参数。我们进行了一项模拟研究，以比较参数的真实值和估计值。此外，我们还将这些模型应用于 McGilchrist 和 Aisbett（1991 年）与肾脏感染数据相关的真实二元生存数据集，并为该数据提出了一个更好的模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Analysis of kidney infection data using correlated compound poisson frailty models

Shared frailty models are used despite their limitations. To overcome their disadvantages correlated frailty models may be used. In this paper, we introduce the correlated compound Poisson frailty models with two different baseline distributions namely, the generalized log logistic and the generalized Weibull. We introduce the Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. Also we apply these models to a real life bivariate survival data set of McGilchrist and Aisbett (1991) related to the kidney infection data and a better model is suggested for the data.

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来源期刊

Model Assisted Statistics and Applications Mathematics-Applied Mathematics

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.