Sample Size Calculations for Time-Averaged Difference of Longitudinal Binary Outcomes [0.03%]
纵向二分类结局时间累积差的样本量计算方法研究
Ying Lou,Jing Cao,Song Zhang et al.
Ying Lou et al.
In clinical trials with repeated measurements, the responses from each subject are measured multiple times during the study period. Two approaches have been widely used to assess the treatment effect, one that compares the rate of change be...
Orthogonality of the Mean and Error Distribution in Generalized Linear Models [0.03%]
广义线性模型中均值与误差分布的正交性
Alan Huang,Paul J Rathouz
Alan Huang
We show that the mean-model parameter is always orthogonal to the error distribution in generalized linear models. Thus, the maximum likelihood estimator of the mean-model parameter will be asymptotically efficient regardless of whether the...
Consistent model identification of varying coefficient quantile regression with BIC tuning parameter selection [0.03%]
具备BIC调参选择的可变系数分位数回归模型的稳定识别
Qi Zheng,Limin Peng
Qi Zheng
Quantile regression provides a flexible platform for evaluating covariate effects on different segments of the conditional distribution of response. As the effects of covariates may change with quantile level, contemporaneously examining a ...
Jiao Jin,Liang Zhu,Xingwei Tong et al.
Jiao Jin et al.
In this paper, we consider a linear model in which the covariates are measured with errors. We propose a t-type corrected-loss estimation of the covariate effect, when the measurement error follows the Laplace distribution. The proposed est...
Vidhura Tennekoon,Robert Rosenman
Vidhura Tennekoon
When a binary dependent variable is misclassified, that is, recorded in the category other than where it really belongs, probit and logit estimates are biased and inconsistent. In some cases the probability of misclassification may vary sys...
A Smooth Bootstrap Procedure towards Deriving Confidence Intervals for the Relative Risk [0.03%]
一种导出相对风险置信区间的平滑自助法程序
Dongliang Wang,Alan D Hutson
Dongliang Wang
Given a pair of sample estimators of two independent proportions, bootstrap methods are a common strategy towards deriving the associated confidence interval for the relative risk. We develop a new smooth bootstrap procedure, which generate...
Inversion Theorem Based Kernel Density Estimation for the Ordinary Least Squares Estimator of a Regression Coefficient [0.03%]
基于逆定理的核密度估计在回归系数的普通最小二乘估计中的应用
Dongliang Wang,Alan D Hutson
Dongliang Wang
The traditional confidence interval associated with the ordinary least squares estimator of linear regression coefficient is sensitive to non-normality of the underlying distribution. In this article, we develop a novel kernel density estim...
An Investigation of Quantile Function Estimators Relative to Quantile Confidence Interval Coverage [0.03%]
分位数置信区间覆盖率下的分位数函数估计方法研究
Lai Wei,Dongliang Wang,Alan D Hutson
Lai Wei
In this article, we investigate the limitations of traditional quantile function estimators and introduce a new class of quantile function estimators, namely, the semi-parametric tail-extrapolated quantile estimators, which has excellent pe...
Quantifying the Impact of Unobserved Heterogeneity on Inference from the Logistic Model [0.03%]
未观察到的异质性对逻辑斯蒂模型推断的影响量化研究
Salma Ayis
Salma Ayis
While consequences of unobserved heterogeneity such as biased estimates of binary response regression models are generally known; quantifying these and awareness of situations with more serious impact on inference is however, remarkably lac...
Hyunsu Ju
Hyunsu Ju
In a longitudinal study subjects are followed over time. I focus on a case where the number of replications over time is large relative to the number of subjects in the study. I investigate the use of moving block bootstrap methods for anal...