Pao-Sheng Shen
Pao-Sheng Shen
In this note, we consider data subjected to middle censoring where the variable of interest becomes unobservable when it falls within an interval of censorship. We demonstrate that the nonparametric maximum likelihood estimator (NPMLE) of d...
Dongliang Wang,Tong Tong Wu,Yichuan Zhao
Dongliang Wang
The current penalized regression methods for selecting predictor variables and estimating the associated regression coefficients in the sparse Cox model are mainly based on partial likelihood. In this paper, a bias-corrected empirical likel...
Kim May Lee,James Wason
Kim May Lee
Precision medicine, aka stratified/personalized medicine, is becoming more pronounced in the medical field due to advancement in computational ability to learn about patient genomic backgrounds. A biomaker, i.e. a type of biological process...
A group analysis using the Multiregression Dynamic Models for fMRI networked time series [0.03%]
基于功能磁共振图像网络时间序列的多回归动态模型群组分析方法研究
Lilia Costa,James Q Smith,Thomas Nichols
Lilia Costa
Connectivity studies of the brain are usually based on functional Magnetic Resonance Imaging (fMRI) experiments involving many subjects. These studies need to take into account not only the interaction between areas of a single brain but al...
Latent class based multiple imputation approach for missing categorical data [0.03%]
基于潜在类别模型的定性缺失数据多重插补方法研究
Mulugeta Gebregziabher,Stacia M DeSantis
Mulugeta Gebregziabher
In this paper we propose a latent class based multiple imputation approach for analyzing missing categorical covariate data in a highly stratified data model. In this approach, we impute the missing data assuming a latent class imputation m...
Statistical Power in Two-Level Hierarchical Linear Models with Arbitrary Number of Factor Levels [0.03%]
任意水平个数的两层分层线性模型中的统计功效分析
Yongyun Shin,Jennifer Elston Lafata,Yu Cao
Yongyun Shin
As the US health care system undergoes unprecedented changes, the need for adequately powered studies to understand the multiple levels of main and interaction factors that influence patient and other care outcomes in hierarchical settings ...
Jacob M Maronge,Yi Zhai,Douglas P Wiens et al.
Jacob M Maronge et al.
In this article we investigate the optimal design problem for some wavelet regression models. Wavelets are very flexible in modeling complex relations, and optimal designs are appealing as a means of increasing the experimental precision. I...
Robust bent line regression [0.03%]
稳健的折线回归模型
Feipeng Zhang,Qunhua Li
Feipeng Zhang
We introduce a rank-based bent linear regression with an unknown change point. Using a linear reparameterization technique, we propose a rank-based estimate that can make simultaneous inference on all model parameters, including the locatio...
Lu Wang,Yong Chen,Hongjian Zhu
Lu Wang
Modern clinical trials are often complex, with multiple competing objectives and multiple endpoints. Such trials should be both ethical and efficient. In this paper, we overcome the obstacles introduced by the large number of unknown parame...
Gang Shen,Seung Won Hyun,Weng Kee Wong
Gang Shen
We use optimal design theory and construct locally optimal designs based on the maximum quasi-likelihood estimator (MqLE), which is derived under less stringent conditions than those required for the MLE method. We show that the proposed lo...