论文检索

The purpose of this note is to show how semiparametric estimators with a small bias property can be constructed. The small bias property (SBP) of a semiparametric estimator is that its bias converges to zero faster than the pointwise and integrated bias of the nonparametric estimator on which it is based. We show that semiparametric estimators based on twicing kernels have the SBP. We also show that semiparametric estimators where nonparametric kernel estimation does not…

异质风险率回归模型：理论与应用AI 解读

Summary A class of non-proportional hazards regression models is considered to have hazard specifications consisting of a power form of cross-effects on the base-line hazard function. The primary goal of these models is to deal with settings in which heterogeneous distribution shapes of survival times may be present in populations characterized by some observable covariates. Although effects of such heterogeneity can be explicitly seen through crossing cumulative hazards…

删失同方差线性回归的估计：经验过程方法AI 解读

Pertaining to the estimating equations proposed by Tsiatis, based on the linear rank test, we show the existence of local confounding between the baseline hazard function and the covariates. Due to the local confounding, an estimating equation in Tsiatis' family with a larger time point of truncation could contain less information about the regression parameter than the estimating equation with a smaller time point of truncation. This phenomenon further indicates significant…

删失数据两样本位置—尺度模型的经验过程方法AI 解读

To compare two samples of possibly right-censored failure times, a location-scale model, without assuming the distribution form, is considered for the log-transformed data. This new accelerated failure time model is introduced to accommodate the possible heterogeneity between within-treatment variations of the two groups considered. One distinct feature of this model is that, with the presence of heterogeneity, statistical inferences on both location and scale parameters…

受试者工作特征曲线的非参数与半参数估计AI 解读

The receiver operating characteristic (ROC) curve describes the performance of a diagnostic test used to discriminate between healthy and diseased individuals based on a variable measured on a continuous scale. The data consist of a training set of m responses $X_1, \dots, X_m$ from healthy individuals and n responses $Y_1, \dots, Y_n$ from diseased individuals. The responses are assumed i.i.d. from unknown distributions F and G, respectively. We consider estimation of the…

两条生存曲线的变换模型：经验过程方法AI 解读

A new transformation model for two survival curves with possibly nonproportional hazards is presented. The model assumes the existence of an unknown transformation of the survival curves into Weibull distributions with different shape parameters. The partial likelihood approach fails in the model. A new method of estimation called the empirical process approach is proposed. This approach is based on the strong approximation of the Kaplan-Meier product-limit estimators and…

异质处理效应下半参数两样本模型的经验过程方法AI 解读

SUMMARY Two types of semiparametric model are proposed for comparing two samples with possibly heterogeneous treatment effects. One model is a two-sample location-scale model which assumes that the Q-Q-plot of the two distributions involved is linear; the other is the class of two-sample transformation models which assume parametric forms for a probability plot—the receiver operating characteristic curve. The empirical process approach is used to construct strong…

协变量缺失或误测时条件密度的半参数有效估计AI 解读

SUMMARY Pepe and Fleming, and Carroll and Wand have recently proposed estimators in a parametric model for the density of a random variable Y conditional on a vector of covariates (X, V) when data on one of the regressors X is missing for some study subjects. We propose a new class of estimators that remains consistent and asymptotically normal even when the probability that X is missing depends on the observed V and Y, includes an estimator whose asymptotic variance attains…