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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Modelling and estimating heterogeneous variances in threshold models for ordinal discrete data via Winbugs/Openbugs.
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Modelling and estimating heterogeneous variances in threshold models for ordinal discrete data via Winbugs/Openbugs.

机译：通过Winbugs / Openbugs对有序离散数据的阈值模型进行建模和估计异构方差。

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摘要

Analysis of discrete repeated outcomes is an important issue in biomedical studies. The aim of this paper is to propose a flexible and parsimonious model to account for heterogeneous variances for discrete outcomes. The proposed method is based on the use of a linear mixed model on the log of the standard deviation parameters. It is also shown how parameter estimation in this model can be performed with an exact procedure based on a Gibbs sampling algorithm implemented with the Winbugs/Openbugs software. A model comparison study is presented to illustrate the efficiency of this procedure using a well known example from the clinical trial literature. It was found that the proposed methodology considerably improved the predictive ability of the model while remaining very parsimonious. In particular, it was found that adding a random subject effect in the variance model significantly improved the posterior predictive p-value criterion of the model.
机译：离散重复结果的分析是生物医学研究中的重要问题。本文的目的是提出一个灵活且简约的模型，以解决离散结果的异构方差。所提出的方法基于对标准偏差参数的对数使用线性混合模型。还显示了如何使用基于Winbugs / Openbugs软件实现的Gibbs采样算法的精确过程执行此模型中的参数估计。提出了一个模型比较研究，以使用临床试验文献中的一个众所周知的例子来说明此程序的效率。发现所提出的方法极大地提高了模型的预测能力，同时保持了非常简约的效果。特别地，发现在方差模型中添加随机对象效应显着改善了模型的后验预测p值标准。

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