Semiparametric linear transformation models serve as useful alternatives to the Cox proportional hazard model. In this study, we use the semiparametric linear transformation model to analyze survival data with selective compliance. We estimate regression parameters and the transformation function based on pseudo‐likelihood and a series of estimating equations. We show that the estimators for the regression parameters and transformation function are consistent and asymptotically normal, and both converge to their true values at the rate of , the convergence rate expected for a parametric model. The practical utility of the methods is confirmed via simulations as well as an application of a clinical trial to evaluate the effectiveness of sentinel node biopsy in guiding the treatment of invasive melanoma. The Canadian Journal of Statistics 42: 18–35; 2014 © 2013 Statistical Society of Canada

中文翻译：

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半参数线性变换模型，用于估计生存数据的因果效应。

半参数线性变换模型可以用作Cox比例风险模型的有用替代方法。在这项研究中，我们使用半参数线性变换模型来分析具有选择性依从性的生存数据。我们根据伪似然和一系列估计方程估算回归参数和变换函数。我们表明，回归参数和变换函数的估计量是一致的，并且渐近是正态的，并且两者均以参数模型预期的收敛速度的速率收敛到其真实值。该方法的实用性通过模拟以及临床试验的应用得到了证实，该临床试验用于评估前哨淋巴结活检在指导浸润性黑色素瘤治疗中的有效性。《加拿大统计杂志》 42：18–35；2014©2013加拿大统计学会