Chun Yu,Weixin Yao,Kun Chen
Chun Yu
Finite mixture regression models have been widely used for modelling mixed regression relationships arising from a clustered and thus heterogenous population. The classical normal mixture model, despite its simplicity and wide applicability...
Bryan E Shepherd,Chun Li,Qi Liu
Bryan E Shepherd
We describe a new residual for general regression models, defined as pr(Y* < y) - pr(Y* > y), where y is the observed outcome and Y* is a random variable from the fitted distribution. This probability-scale residual can be written as E {sig...
A semivarying joint model for longitudinal binary and continuous outcomes [0.03%]
具有纵向二元和连续结果的半变联合模型
Esra Kürüm,John Hughes,Runze Li
Esra Kürüm
Semivarying models extend varying coefficient models by allowing some regression coefficients to be constant with respect to the underlying covariate(s). In this paper we develop a semivarying joint modelling framework for estimating the ti...
Variable Selection and Inference Procedures for Marginal Analysis of Longitudinal Data with Missing Observations and Covariate Measurement Error [0.03%]
具有缺失观测值和协变量测量误差的纵向数据边缘分析的变量选择和推理方法
Grace Y Yi,Xianming Tan,Runze Li
Grace Y Yi
In contrast to extensive attention on model selection for univariate data, research on model selection for longitudinal data remains largely unexplored. This is particularly the case when data are subject to missingness and measurement erro...
Statistical inference for the additive hazards model under outcome-dependent sampling [0.03%]
具有结果相关样本的加性风险模型的统计推断
Jichang Yu,Yanyan Liu,Dale P Sandler et al.
Jichang Yu et al.
Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) desi...
Ruzong Fan,Bin Zhu,Yuedong Wang
Ruzong Fan
In this article, we establish a connection between a stochastic dynamic model (SDM) driven by a linear stochastic differential equation (SDE) and a Chebyshev spline, which enables researchers to borrow strength across fields both theoretica...
Lihui Zhao,X Joan Hu
Lihui Zhao
The semi-Markov process often provides a better framework than the classical Markov process for the analysis of events with multiple states. The purpose of this paper is twofold. First, we show that in the presence of right censoring, when ...
Measurement error modeling and nutritional epidemiology association analyses [0.03%]
测量误差模型与营养流行病学关联分析
Ross L Prentice,Ying Huang
Ross L Prentice
This paper summarizes the results of a Nutrient Biomarker Study in the Women's Health Initiative, and its application to studies of the association between energy and protein consumption and the risk of major cancers and cardiovascular dise...
Parallelism, uniqueness, and large-sample asymptotics for the Dantzig selector [0.03%]
丹齐格选择器的平行性、唯一性和大样本渐近性
Lee Dicker,Xihong Lin
Lee Dicker
The Dantzig selector (Candès and Tao, 2007) is a popular ℓ1-regularization method for variable selection and estimation in linear regression. We present a very weak geometric condition on the observed predictors which is related to parall...
Variable selection and estimation in generalized linear models with the seamless L0 penalty [0.03%]
具有一体化L0惩罚的广义线性模型中的变量选择和估计
Zilin Li,Sijian Wang,Xihong Lin
Zilin Li
In this paper, we propose variable selection and estimation in generalized linear models using the seamless L0 (SELO) penalized likelihood approach. The SELO penalty is a smooth function that very closely resembles the discontinuous L0 pena...