Forrest W Crawford,Timothy C Stutz,Kenneth Lange
Forrest W Crawford
Birth-death processes are continuous-time Markov counting processes. Approximate moments can be computed by truncating the transition rate matrix. Using a coupling argument, we derive bounds for the total variation distance between the proc...
Peter M Aronow,Forrest W Crawford
Peter M Aronow
We detail nonparametric identification results for respondent-driven sampling when sampling probabilities are assumed to be functions of network degree known to scale. We show that the conditions for consistency of the Volz-Heckathorn estim...
Joseph Rigdon,Michael G Hudgens
Joseph Rigdon
For two-stage randomized experiments assuming partial interference, exact confidence intervals are proposed for treatment effects on a binary outcome. Empirical studies demonstrate the new intervals have narrower width than previously propo...
Direct formulation to Cholesky decomposition of a general nonsingular correlation matrix [0.03%]
一般非奇异相关矩阵的Cholesky分解的直接公式
Vered Madar
Vered Madar
We present two novel and explicit parametrizations of Cholesky factor of a nonsingular correlation matrix. One that uses semi-partial correlation coefficients, and a second that utilizes differences between the successive ratios of two dete...
Ian W McKeague
Ian W McKeague
Several relativistic extensions of the Maxwell-Boltzmann distribution have been proposed, but they do not explain observed lognormal tail-behavior in the flux distribution of various astrophysical sources. Motivated by this question, extens...
Optimal restricted estimation for more efficient longitudinal causal inference [0.03%]
更有效的纵向因果推断的限制估计方法研究
Edward H Kennedy,Marshall M Joffe,Dylan S Small
Edward H Kennedy
Efficient semiparametric estimation of longitudinal causal effects is often analytically or computationally intractable. We propose a novel restricted estimation approach for increasing efficiency, which can be used with other techniques, i...
A Modified Adaptive Lasso for Identifying Interactions in the Cox Model with the Heredity Constraint [0.03%]
一种改良的自适应LASSO方法在Cox模型中用于具有遗传约束条件下的交互作用识别
Lu Wang,Jincheng Shen,Peter F Thall
Lu Wang
In many biomedical studies, identifying effects of covariate interactions on survival is a major goal. Important examples are treatment-subgroup interactions in clinical trials, and gene-gene or gene-environment interactions in genomic stud...
Michael A Proschan,Pamela A Shaw
Michael A Proschan
The Bonferroni adjustment is sometimes used to control the familywise error rate (FWE) when the number of comparisons is huge. In genome wide association studies, researchers compare cases to controls with respect to thousands of single nuc...
On penalized likelihood estimation for a non-proportional hazards regression model [0.03%]
带罚函数的非比例风险模型的似然估计法
Karthik Devarajan,Nader Ebrahimi
Karthik Devarajan
In this paper, a semi-parametric generalization of the Cox model that permits crossing hazard curves is described. A theoretical framework for estimation in this model is developed based on penalized likelihood methods. It is shown that the...
Jing Qian,Rebecca A Betensky
Jing Qian
Clinical studies using complex sampling often involve both truncation and censoring, where there are options for the assumptions of independence of censoring and event and for the relationship between censoring and truncation. In this paper...