论文检索

整群抽样调查无应答的校准倾向评分方法AI 解读

Weighting adjustment is commonly used in survey sampling to correct for unit nonresponse. In cluster sampling, the missingness indicators are often correlated within clusters and the response mechanism is subject to cluster-specific nonignorable missingness. Based on a parametric working model for the response mechanism that incorporates cluster-specific nonignorable missingness, we propose a method of weighting adjustment. We provide a consistent estimator of the mean or…

降秩惩罚样条平滑的边际方法及其多层函数数据应用AI 解读

Multilevel functional data is collected in many biomedical studies. For example, in a study of the effect of Nimodipine on patients with subarachnoid hemorrhage (SAH), patients underwent multiple 4-hour treatment cycles. Within each treatment cycle, subjects' vital signs were reported every 10 minutes. This data has a natural multilevel structure with treatment cycles nested within subjects and measurements nested within cycles. Most literature on nonparametric analysis of…

协变量缺失下Cox回归的重加权估计AI 解读

Missingness in covariates is a common problem in survival data. In this article we propose a reweighting method for estimating the regression parameters in the Cox model with missing covariates. We also consider the augmented reweighting method by subtracting the projection term onto the nuisance tangent space. The proposed method provides consistent and asymptotically normally distributed estimators when the missing-data mechanism depends on the outcome variables, as well…

数据并非完全随机缺失时的广义估计方程方法AI 解读

We propose two methods for handling missing data in generalized estimating equation (GEE) analyses: mean imputation and multiple imputation. Each provides valid GEE estimates when data are missing at random. Missing outcomes are imputed sequentially starting from the outcome nearest in time to the observed outcome. The estimators from the two kinds of imputation are compared with the weighting method of Robins et al. We show that multiple imputation with an infinite number…