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Linear Regression Modeling of Interval-censored Survival Times Based on a Convex Piecewise-linear Criterion Function

机译:基于凸分段线性准则函数的区间删失生存时间线性回归建模

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Regression models of censored survival data are often required to handle the cases, where information on the dependent (response) variable is only available as intervals, within which the actual values are located. We report on implementation and some preliminary tests of a new general method for regression with an interval-censored response variable. This method is based on minimization of a convex piecewise-linear (CPL) criterion function introduced earlier for perceptron-type classifier design. The presented interval regression method (CPL-IR) can handle arbitrary pattern of exact and left-, right-, or interval-censored data in one flexible computational framework.
机译:通常需要经过审查的生存数据的回归模型来处理这种情况,其中因变量(响应)的信息仅作为间隔(实际值位于该间隔内)可用。我们报告了一种新的具有间隔审查的响应变量的通用回归方法的实施情况和一些初步测试。该方法基于最小化的先前引入感知器类型分类器设计的凸分段线性(CPL)标准函数。提出的间隔回归方法(CPL-IR)可以在一个灵活的计算框架中处理任意模式的精确数据和左,右或间隔检查的数据。

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