Banerjee Tathagata, Chen Ming-Hui, Dey Dipak K, Kim Sungduk
Department of Statistics, Calcutta University, Calcutta, 700019, India.
Lifetime Data Anal. 2007 Jun;13(2):241-60. doi: 10.1007/s10985-007-9035-3. Epub 2007 Mar 31.
In the analysis of censored survival data Cox proportional hazards model (1972) is extremely popular among the practitioners. However, in many real-life situations the proportionality of the hazard ratios does not seem to be an appropriate assumption. To overcome such a problem, we consider a class of nonproportional hazards models known as generalized odds-rate class of regression models. The class is general enough to include several commonly used models, such as proportional hazards model, proportional odds model, and accelerated life time model. The theoretical and computational properties of these models have been re-examined. The propriety of the posterior has been established under some mild conditions. A simulation study is conducted and a detailed analysis of the data from a prostate cancer study is presented to further illustrate the proposed methodology.
在截尾生存数据的分析中，Cox比例风险模型（1972）在从业者中极为流行。然而，在许多实际情况中，风险比的比例性似乎并不是一个合适的假设。为了克服这个问题，我们考虑一类非比例风险模型，称为广义比值率回归模型。该类别足够通用，包括几个常用模型，如比例风险模型、比例优势模型和加速寿命模型。这些模型的理论和计算特性已经重新审视。在一些温和条件下建立了后验的恰当性。进行了模拟研究，并对一项前列腺癌研究的数据进行了详细分析，以进一步说明所提出的方法。
