Exact tests using binary data in adaptive two or multi-stage designs [0.03%]
自适应两阶段或多元设计中使用二值数据的精确检验方法
Huan Yin,Weizhen Wang,Zhongzhan Zhang
Huan Yin
When establishing an effective treatment with binary data in a two-stage design, one-sided tests for a proportion p are employed. Researchers use the parameter configuration at the boundary of the null hypothesis space to determine a reject...
Daiane A Zuanetti,Júlia M Pavan Soler,José E Krieger et al.
Daiane A Zuanetti et al.
QTL mapping is an important tool for identifying regions in chromosomes which are relevant to explain a response of interest. It is a special case of the regression model where an unknown number of missing (non-observable) covariates is inv...
Random forests for homogeneous and non-homogeneous Poisson processes with excess zeros [0.03%]
含零膨胀的齐次与非齐次泊松过程的随机森林方法
Walid Mathlouthi,Denis Larocque,Marc Fredette
Walid Mathlouthi
We propose a general hurdle methodology to model a response from a homogeneous or a non-homogeneous Poisson process with excess zeros, based on two forests. The first forest in the two parts model is used to estimate the probability of havi...
Sampling-based Markov regression model for multistate disease progression: Applications to population-based cancer screening program [0.03%]
基于样本的马尔可夫回归模型在多状态疾病进展中的应用：用于人群癌症筛查项目
Chen-Yang Hsu,Wen-Feng Hsu,Amy Ming-Fang Yen et al.
Chen-Yang Hsu et al.
To develop personalized screening and surveillance strategies, the information required to superimpose state-specific covariates into the multi-step progression of disease natural history often relies on the entire population-based screenin...
Statistical tests for latent class in censored data due to detection limit [0.03%]
检测限截尾数据的潜类别统计检验方法研究
Hua He,Wan Tang,Tanika Kelly et al.
Hua He et al.
Measures of substance concentration in urine, serum or other biological matrices often have an assay limit of detection. When concentration levels fall below the limit, the exact measures cannot be obtained. Instead, the measures are censor...
An adaptive power prior for sequential clinical trials - Application to bridging studies [0.03%]
自适应功效先验在序贯临床试验中的应用-桥接研究为例
Adrien Ollier,Satoshi Morita,Moreno Ursino et al.
Adrien Ollier et al.
During drug evaluation trials, information from clinical trials previously conducted on another population, indications or schedules may be available. In these cases, it might be desirable to share information by efficiently using the avail...
Penalized estimation of semiparametric transformation models with interval-censored data and application to Alzheimer's disease [0.03%]
间断数据半参变换模型的惩罚估计及其在阿尔茨海默病研究中的应用
Shuwei Li,Qiwei Wu,Jianguo Sun
Shuwei Li
Variable selection or feature extraction is fundamental to identify important risk factors from a large number of covariates and has applications in many fields. In particular, its applications in failure time data analysis have been recogn...
Weighted cumulative sum tests for random effect models with binary responses [0.03%]
具有二值响应的随机效应模型的加权累积和检验
Antonia K Korre,Vassilis Gs Vasdekis
Antonia K Korre
Correlated binary responses are very commonly encountered in many disciplines like, for example, medical studies. The development of goodness-of-fit tests is essential for examining the adequacy of the fitted models. The objective of this a...
Confidence intervals for the ratio of two independent Poisson rates: Parametric bootstrap, modified asymptotic, and approximate-estimate approaches [0.03%]
两独立Poission率比的置信区间：参数靴带、改进渐近和近似估计方法
Mahmood Kharrati-Kopaei,Raziye Dorosti-Motlagh
Mahmood Kharrati-Kopaei
We propose four confidence intervals for the ratio of two independent Poisson rates. We apply a parametric bootstrap approach, two modified asymptotic results, and we propose an ad-hoc approximate-estimate method to construct confidence int...
The impact of unmeasured within- and between-cluster confounding on the bias of effect estimatorsof a continuous exposure [0.03%]
未测量的聚集内和聚集间偏倚对连续暴露因素影响估计值的影响
Yun Li,Yoonseok Lee,Friedrich K Port et al.
Yun Li et al.
Unmeasured confounding almost always exists in observational studies and can bias estimates of exposure effects. Instrumental variable methods are popular choices in combating unmeasured confounding to obtain less biased effect estimates. H...