Statistical Inference for Cox Proportional Hazards Models with a Diverging Number of Covariates [0.03%]
Cox比例 Hazard模型的条件准最大似然估计及其推断（渐近性质）
Lu Xia,Bin Nan,Yi Li
Lu Xia
For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher information matrix. Such assumptions, however, are often violate...
Nonparametric bounds for the survivor function under general dependent truncation [0.03%]
一般相依截尾下生存函数的非参数界估计
Jing Qian,Rebecca A Betensky
Jing Qian
Truncation occurs in cohort studies with complex sampling schemes. When truncation is ignored or incorrectly assumed to be independent of the event time in the observable region, bias can result. We derive completely nonparametric bounds fo...
Multiply robust matching estimators of average and quantile treatment effects [0.03%]
多重稳健的匹配估计量：对平均和分位数处理效应的估计
Shu Yang,Yunshu Zhang
Shu Yang
Propensity score matching has been a long-standing tradition for handling confounding in causal inference, however requiring stringent model assumptions. In this article, we propose novel double score matching (DSM) utilizing both the prope...
Yunwei Cui,Rongning Wu,Qi Zheng
Yunwei Cui
We apply a three-step sequential procedure to estimate the change-point of count time series. Under certain regularity conditions, the estimator of change-point converges in distribution to the location of the maxima of a two-sided random w...
Optimal Estimator for Logistic Model with Distribution-free Random Intercept [0.03%]
无分布假设随机截距的逻辑斯谛模型的最优估计方法
Tanya P Garcia,Yanyuan Ma
Tanya P Garcia
Logistic models with a random intercept are prevalent in medical and social research where clustered and longitudinal data are often collected. Traditionally, the random intercept in these models is assumed to follow some parametric distrib...
Lan Wen,Miguel A Hernán,James M Robins
Lan Wen
Multiply robust estimators of the longitudinal g-formula have recently been proposed to protect against model misspecification better than the standard augmented inverse probability weighted estimator (Rotnitzky et al., 2017; Luedtke et al....
Efficiency of Naive Estimators for Accelerated Failure Time Models under Length-Biased Sampling [0.03%]
长度偏差抽样下加速失效时间模型的朴素估计的有效性研究
Pourab Roy,Jason P Fine,Michael R Kosorok
Pourab Roy
In prevalent cohort studies where subjects are recruited at a cross-section, the time to an event may be subject to length-biased sampling, with the observed data being either the forward recurrence time, or the backward recurrence time, or...
Jing Zhang,Haibo Zhou,Yanyan Liu et al.
Jing Zhang et al.
Case-cohort design has been demonstrated to be an economical and efficient approach in large cohort studies when the measurement of some covariates on all individuals is expensive. Various methods have been proposed for case-cohort data whe...
Stochastic Functional Estimates in Longitudinal Models with Interval-Censored Anchoring Events [0.03%]
纵向模型中区间截断锚定事件的随机函数估计
Chenghao Chu,Ying Zhang,Wanzhu Tu
Chenghao Chu
Timelines of longitudinal studies are often anchored by specific events. In the absence of fully observed the anchoring event times, the study timeline becomes undefined, and the traditional longitudinal analysis loses its temporal referenc...
Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework [0.03%]
基于总体模型框架的预测均值匹配插补的渐近理论与推断
Shu Yang,Jae Kwang Kim
Shu Yang
Predictive mean matching imputation is popular for handling item nonresponse in survey sampling. In this article, we study the asymptotic properties of the predictive mean matching estimator for finite-population inference using a superpopu...