论文部分内容阅读
Bayesian Logistic Regression Model(BLRM)is an adaptive dose escalation scheme newly developed in phase oncology clinical trials.
Bridging Study in Dose Finding Using Bayesian Logistic Regression Models
【摘 要】
：
Bayesian Logistic Regression Model(BLRM)is an adaptive dose escalation scheme newly developed in phase oncology clinical trials.
【出 处】
：
上海交通大学
【发表日期】
：
2016年4期
其他文献
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.
Multiparameter local likelihood models and generalizations have been widely applied to analyze relationship between responses and covariates in data arising from climatology,econometrics,environmetric
A common problem that is encountered in many medical applications is the comparison of two cumulative incidence functions(CIFs)in the presence of competing risks.
Advances in biotechnology have culminated in the development of large scale genetic and sequencing association studies.
Let {Zij} be independent and identically distributed(i.i.d.)random variables with EZij = 0,E|Zij|2 = 1 and E|Zij |4 < ∞.