The Cox proportional hazards model has been widely used for modeling response-time data in educational and psychological research. However, based on the Kaplan-Meier (KM) plots in an empirical example, we find that the proportionality of the hazard ratios does not seem to be an appropriate assumption, and there are considerable differences in survival rates among different items. To overcome such a problem, we consider a class of flexible nonproportional hazards models known as the generalized odds-rate hazards class of regression models. This class is general enough to include several commonly used models, including the proportional hazards model and the proportional odds model, as special cases. A fully Bayesian method is developed for parameter estimation and the deviance information criterion (DIC) and the logarithm of the pseudomarginal likelihood (LPML) are employed for model comparison. Simulation studies are conducted and a detailed analysis of the Programme for International Student Assessment (PISA) science data is carried out to further illustrate the proposed methodology.

中文翻译：

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一种用于联合分析计算机测试响应时间和准确性的广义半参数模型

Cox 比例风险模型已广泛用于对教育和心理学研究中的响应时间数据进行建模。然而，基于一个经验示例中的 Kaplan-Meier (KM) 图，我们发现风险比的比例似乎不是一个合适的假设，不同项目之间的存活率存在相当大的差异。为了克服这个问题，我们考虑一类灵活的非比例风险模型，称为回归模型的广义优势率风险类。这个类足够通用，包括几个常用的模型，包括比例风险模型和比例优势模型，作为特殊情况。开发了一种完全贝叶斯方法用于参数估计，并采用偏差信息准则 (DIC) 和伪边际似然对数 (LPML) 进行模型比较。进行了模拟研究，并对国际学生评估计划 (PISA) 的科学数据进行了详细分析，以进一步说明所提出的方法。