论文部分内容阅读
Can Blinded Safety Review Be Informative?--How to decipher safety information from Blinded Data?
【出 处】
：
上海交通大学
【发表日期】
：
2016年4期
其他文献
The biomedical field has recently focused on developing targeted therapies,designed to be effective in only some subset of the population with a given disease.
Modern high throughput biotechnologies such as microarray and next generation sequencing produce massive amount of information for each sample assayed.
In high-dimensional regression analysis where the number of potential covariates is much larger than the sample size,inference on the support of true coefficients is necessary and crucial.
Excursion probabilities of Gaussian random fields have many applications in statistics(e.g.,scanning statistic and control of false discovery rate(FDR))and in other areas.
Power Calculation of Multi-step Combined Principal Components with Applications to Genetic Associati
Principal component analysis(PCA)is a useful tool to identify important linear combina-tion of correlated variables in multivariate analysis and has been applied to detect association between genetic
We investigate the scenario of selecting variables in both the group level and within-group level simultaneously,in the sense that at most one variable will be selected in each group.
Motivation: In large-scale genetic association studies with tens of hundreds of single nucleotide polymorphisms(SNPs)genotyped,the traditional statistical framework of logistic regression using maximu
With the help of distributed sensing and high-speed wireless communication technologies,real-time data collection in complex systems is becoming more and more common.
Estimating treatment importance in multi-drug-resistant tuberculosis using Targeted Learning:an obse
Multi-drug-resistant tuberculosis(MDR-TB)is defined as strains of tuberculosis(TB)that do not respond to at least the two most powerful anti-TB drugs.
A model-assisted nonparametric method is investigated to estimate the finite population totals of spatial survey data over irregularly shaped domains.