Confidence Interval Estimation of the Youden index and corresponding cut-point for a combination of biomarkers under normality [0.03%]
正态性下联合生物标志物Youden指数及对应临界值的置信区间估计
Kristopher Attwood,Lili Tian
Kristopher Attwood
In prognostic/diagnostic medical research, it is often the goal to identify a biomarker that differentiates between patients with and without a condition, or patients that will have good or poor response to a given treatment. The statistica...
ON THE TRACE OF A WISHART [0.03%]
愿境踪迹
Deborah H Glueck,Keith E Muller
Deborah H Glueck
A derivation based on spectral decomposition allows specifying the characteristic function of the trace of a singular or nonsingular, central or noncentral, true or pseudo-Wishart. The trace equals a weighted sum of noncentral chi-squared r...
Ling Chen,Yanqin Feng,Jianguo Sun
Ling Chen
The gap time between recurrent events is often of primary interest in many fields such as medical studies (Cook and Lawless 2007; Kang, Sun, and Zhao 2015; Schaubel and Cai 2004), and in this paper, we discuss regression analysis of the gap...
Covariate adjustment via propensity scores for recurrent events in the presence of dependent censoring [0.03%]
通过倾向评分调整反复事件的协变量依赖性截断情况下的估计问题
Youngjoo Cho,Debashis Ghosh
Youngjoo Cho
Dependent censoring is common in many medical studies, especially when there are multiple occurrences of the event of interest. Ghosh and Lin (2003) and Hsieh, Ding and Wang (2011) proposed estimation procedures using an artificial censorin...
Tao Yang,Colin M Gallagher,Christopher S McMahan
Tao Yang
A robust regression methodology is proposed via M-estimation. The approach adapts to the tail behavior and skewness of the distribution of the random error terms, providing for a reliable analysis under a broad class of distributions. This ...
Exact group sequential designs for two-arm experiments with Poisson distributed outcome variables [0.03%]
两臂试验中具有泊松分布结果变量的精确组序贯设计
Michael J Grayling,James M S Wason,Adrian P Mander
Michael J Grayling
We describe and compare two methods for the group sequential design of two-arm experiments with Poisson distributed data, which are based on a normal approximation and exact calculations respectively. A framework to determine near-optimal s...
Parameter Estimation for Semiparametric Ordinary Differential Equation Models [0.03%]
半参数微分方程模型的参数估计问题
Hongqi Xue,Arun Kumar,Hulin Wu
Hongqi Xue
We propose a new class of two-stage parameter estimation methods for semiparametric ordinary differential equation (ODE) models. In the first stage, state variables are estimated using a penalized spline approach; In the second stage, form ...
Log-epsilon-skew normal: A generalization of the log-normal distribution [0.03%]
对数 epsilon 斜正态分布：对数正态分布的一种拓展形式
Alan D Hutson,Terry L Mashtare Jr,Govind S Mudholkar
Alan D Hutson
The log-normal distribution is widely used to model non-negative data in many areas of applied research. In this paper, we introduce and study a family of distributions with non-negative reals as support and termed the log-epsilon-skew norm...
Sample Size Calculation for Count Outcomes in Cluster Randomization Trials with Varying Cluster Sizes [0.03%]
集群大小不等的集群随机对照试验中的计数结果样本量计算方法
Jijia Wang,Song Zhang,Chul Ahn
Jijia Wang
In many cluster randomization studies, cluster sizes are not fixed and may be highly variable. For those studies, sample size estimation assuming a constant cluster size may lead to under-powered studies. Sample size formulas have been deve...
Estimation of Multi-state Models with Missing Covariate Values Based on Observed Data Likelihood [0.03%]
基于观测数据似然的缺失协变量多状态模型估计方法
Wenjie Lou,Erin L Abner,Lijie Wan et al.
Wenjie Lou et al.
Continuous-time multi-state models are commonly used to study diseases with multiple stages. Potential risk factors associated with the disease are added to the transition intensities of the model as covariates, but missing covariate measur...