Does Finasteride Affect the Severity of Prostate Cancer? A Causal Sensitivity Analysis [0.03%]
非那雄胺是否影响前列腺癌的严重程度？因果敏感性分析
Bryan E Shepherd,Mary W Redman,Donna P Ankerst
Bryan E Shepherd
In 2003 Thompson and colleagues reported that daily use of finasteride reduced the prevalence of prostate cancer by 25% compared to placebo. These results were based on the double-blind randomized Prostate Cancer Prevention Trial (PCPT) whi...
Raymond J Carroll,Aurore Delaigle,Peter Hall
Raymond J Carroll
Predicting the value of a variable Y corresponding to a future value of an explanatory variable X, based on a sample of previously observed independent data pairs (X(1), Y(1)), …, (X(n), Y(n)) distributed like (X, Y), is very important in ...
An Incomplete-Data Quasi-likelihood Approach to Haplotype-Based Genetic Association Studies on Related Individuals [0.03%]
一种基于亲缘个体的基因型数据开展位相型遗传关联分析的方法研究
Zuoheng Wang,Mary Sara McPeek
Zuoheng Wang
We propose an incomplete-data, quasi-likelihood framework, for estimation and score tests, which accommodates both dependent and partially-observed data. The motivation comes from genetic association studies, where we address the problems o...
Miles S Kimball,Claudia R Sahm,Matthew D Shapiro
Miles S Kimball
Economic theory assigns a central role to risk preferences. This article develops a measure of relative risk tolerance using responses to hypothetical income gambles in the Health and Retirement Study. In contrast to most survey measures th...
Incorporating Historical Control Data When Comparing Tumor Incidence Rates [0.03%]
结合历史对照数据比较肿瘤发病率时的考量因素
Shyamal D Peddada,Gregg E Dinse,Grace E Kissling
Shyamal D Peddada
Animal carcinogenicity studies, such as those conducted by the U.S. National Toxicology Program (NTP), focus on detecting trends in tumor rates across dose groups. Over time, the NTP has compiled vast amounts of data on tumors in control an...
Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data [0.03%]
具有空间相关性的分层函数数据的降秩混合效应模型
Lan Zhou,Jianhua Z Huang,Josue G Martinez et al.
Lan Zhou et al.
Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: withi...
Penalized Estimating Functions and Variable Selection in Semiparametric Regression Models [0.03%]
惩罚似然和半参数回归模型中的变量选择
Brent A Johnson,D Y Lin,Donglin Zeng
Brent A Johnson
We propose a general strategy for variable selection in semiparametric regression models by penalizing appropriate estimating functions. Important applications include semiparametric linear regression with censored responses and semiparamet...
Hao Liu,Yu Shen
Hao Liu
Motivated by medical studies in which patients could be cured of disease but the disease event time may be subject to interval censoring, we presents a semiparametric non-mixture cure model for the regression analysis of interval-censored t...
A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem [0.03%]
一种用于错误变量问题的自适应局部多项式估计器的设计
Aurore Delaigle,Jianqing Fan,Raymond J Carroll
Aurore Delaigle
Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-va...
On Nonparametric Variance Estimation for Second-Order Statistics of Inhomogeneous Spatial Point Processes With a Known Parametric Intensity Form [0.03%]
当齐次空间点过程强度已知时第二阶统计量的非参数方差估计方法研究
Yongtao Guan
Yongtao Guan
We introduce new variance estimation procedures for second-order statistics that are computed from a single realization of intensity reweighted stationary spatial point processes. The statistics are defined either on a subset B of the obser...