Association analyses of clustered competing risks data via cross hazard ratio [0.03%]
基于交叉危险率的聚类竞争风险数据分析
Yu Cheng,Jason P Fine,Karen Bandeen-Roche
Yu Cheng
Bandeen-Roche and Liang (2002, Modelling multivariate failure time associations in the presence of a competing risk. Biometrika 89, 299-314.) tailored Oakes (1989, Bivariate survival models induced by frailties. Journal of the American Stat...
Liansheng Larry Tang,Aiyi Liu
Liansheng Larry Tang
Before a comparative diagnostic trial is carried out, maximum sample sizes for the diseased group and the nondiseased group need to be obtained to achieve a nominal power to detect a meaningful difference in diagnostic accuracy. Sample size...
A hidden Markov random field model for genome-wide association studies [0.03%]
用于全基因组关联研究的隐马尔可夫随机场模型
Hongzhe Li,Zhi Wei,John Maris
Hongzhe Li
Genome-wide association studies (GWAS) are increasingly utilized for identifying novel susceptible genetic variants for complex traits, but there is little consensus on analysis methods for such data. Most commonly used methods include sing...
Semiparametric estimation of the average causal effect of treatment on an outcome measured after a postrandomization event, with missing outcome data [0.03%]
具有一项随机化后事件及缺失结果数据的治疗对结局影响的半参数估计方法研究
Peter B Gilbert,Yuying Jin
Peter B Gilbert
In the past decade, several principal stratification-based statistical methods have been developed for testing and estimation of a treatment effect on an outcome measured after a postrandomization event. Two examples are the evaluation of t...
Trend tests for genetic association using population-based cross-sectional complex survey data [0.03%]
基于人口的横断面复杂调查数据的遗传关联趋势检测方法研究
Dewei She,Yan Li,Hong Zhang et al.
Dewei She et al.
Genetic data collected from surveys such as the Third National Health and Nutrition Examination Survey (NHANES III) enable researchers to investigate the association between wide varieties of health factors and genetic variation for the US ...
Bayesian mixture modeling using a hybrid sampler with application to protein subfamily identification [0.03%]
贝叶斯混合模型的.hybrid算法及其在蛋白质亚家族识别中的应用
Youyi Fong,Jon Wakefield,Kenneth Rice
Youyi Fong
Predicting protein function is essential to advancing our knowledge of biological processes. This article is focused on discovering the functional diversification within a protein family. A Bayesian mixture approach is proposed to model a p...
Modeling between-trial variance structure in mixed treatment comparisons [0.03%]
混合治疗比较中试验间差异方差结构的建模方法研究
Guobing Lu,Ae Ades
Guobing Lu
In mixed treatment comparison (MTC) meta-analysis, modeling the heterogeneity in between-trial variances across studies is a difficult problem because of the constraints on the variances inherited from the MTC structure. Starting from a con...
Comparative Study
Biostatistics (Oxford, England). 2009 Oct;10(4):792-805. DOI:10.1093/biostatistics/kxp032 2009
Estimating dementia-free life expectancy for Parkinson's patients using Bayesian inference and microsimulation [0.03%]
基于贝叶斯推理和微观模拟的帕金森病患者无痴呆生命期望值估计方法研究
Ardo van den Hout,Fiona E Matthews
Ardo van den Hout
Interval-censored longitudinal data taken from a Norwegian study of individuals with Parkinson's disease are investigated with respect to the onset of dementia. Of interest are risk factors for dementia and the subdivision of total life exp...
Bayesian inference for stochastic multitype epidemics in structured populations using sample data [0.03%]
基于样本数据的结构化群体中随机多型流行病的贝叶斯推断方法研究
Philip D O&#x;Neill
Philip D O&#x;Neill
This paper is concerned with the development of new methods for Bayesian statistical inference for structured-population stochastic epidemic models, given data in the form of a sample from a population with known structure. Specifically, th...
Second-order estimating equations for the analysis of clustered current status data [0.03%]
分簇当前状态数据的二阶估计方程分析方法研究
Richard J Cook,David Tolusso
Richard J Cook
With clustered event time data, interest most often lies in marginal features such as quantiles or probabilities from the marginal event time distribution or covariate effects on marginal hazard functions. Copula models offer a convenient f...