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检索条件"任意字段=2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会"

共 22 条记录，以下是11-20 订阅

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Subgroup Analysis in Precision Medicine

Subgroup Analysis in Precision Medicine

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Xuming He Statistics at the University of Michigan

Clinical trials are often used for the assessment of therapeutic *** analysis is routinely used in the clinical studies to understand heterogeneity of treatment effects in subgroups of *** used appropriately,subgroup analysis helps personalized treatments of patients and helps design of new *** used indiscriminately,subgroup analysis leads to costly false *** this lecture,we will introduce(1)post hoc methods for subgroup identification,(2)confirmatory statistical tests for subgroups,and(3)quantitative risk assessment tools for subgroup pursuit by drug developers.

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Propensity Score Methods for Observational Data Analysis

Propensity Score Methods for Observational Data Analysis

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Hongwei Zhao Department of Epidemiology and Biostatistics School of Public HealthTexas A&M University

This three-hour course introduces concepts of potential outcomes and causal effects,and covers propensity score(PS)based methods for making causal inference for observational *** will first discuss the assumptions and the theory for PS based methods,using a real data example to illustrate the steps for different PS based approaches to estimate the causal treatment *** will also introduce other related topics for causal inference,*** marginal structural models and the g-methods for estimating effect modifications and time-varying treatment effects,causal mediation analysis,and instrumental variable methods for handling unmeasured confounding.

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MAGIC:a general,powerful and tractable method for selective inference

MAGIC:a general,powerful and tractable method for selective ...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Xiaoying Tian Nan Bi Jonathan Taylor Department of Statistics Stanford University Sequoia Hall Stanford.CA 94305.USA

Selective inference is a recent research topic that tries to perform valid infer-ence after using the data to select a reasonable statistical *** propose MAGIC,a new method for selective inference that is general,powerful and *** is a method for selective inference after solving a convex optimization problem with smooth loss and?1 *** is incorporated into the optimization prob-lem to boost statistical *** *** reduces the problem into a sampling problem with simple *** applies to many?1 penalized optimization problem including the Lasso,logistic Lasso and neighborhood selection in graphical *** of which we consider in this paper.

关键词： selective inference statistical power sampling

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Recent Development in Analyzing Secondary Phenotype Data under Case-Control Designs

Recent Development in Analyzing Secondary Phenotype Data und...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Dr.Wei Biostatistics at Columbia University

Case-control designs are commonly employed in genetic association *** addition to the case-control status,data on secondary traits are often *** is of interest to take full advantage of the existing data and analyze genetic associations with these additional *** regressing secondary traits on genetic variants from a case-control sample often leads to biased *** this course,we will review and compare the available statistical methods to achieve the unbiased estimation and valid inference for analyzing secondary *** will also go over the computation packages for each *** learning objectives of this course have two folds.(1)The students could understand the statistical methods for analyzing the secondary phenotypes(*** are the assumptions,theories,advantages and limitations associated with each method);(2)The students are able to implement those methods in R for numerical studies and real data applications.

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Variable Selection Diagnostics Measures for High-Dimensional Regression

Variable Selection Diagnostics Measures for High-Dimensional...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Ying NAN Yuhong YANG School of Statistics University of MinnesotaMinneapolisMN 55455

Many exciting results have been obtained on model selection for high-dimensional data in both efficient algorithms and theoretical *** powerful penalized regression methods can give sparse representations of the data even when the number of predictors is much larger than the sample *** important question then is:How do we know when a sparse pattern identified by such a method is reliable?In this work,besides investigating instability of model selection methods in terms of variable selection,we propose variable selection deviation measures that give one a proper sense on how many predictors in the selected set are likely trustworthy in certain *** and a real data example demonstrate the utility of these measures for application.

关键词： Model selection diagnostics Model selection instability Variable selec-tion deviation

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CONFIDENCE SETS FOR MODEL SELECTION BY F-TESTING

CONFIDENCE SETS FOR MODEL SELECTION BY F-TESTING

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Davide Ferrari Yuhong Yang University of Melbourne and University of Minnesota

We introduce the notion of variable selection confidence set(VSCS)for linear regression based on *** method identifies the most important variables in a principled way that goes beyond simply trusting the single winner based on a model selection *** VSCS extends the usual notion of con-fidence intervals to the variable selection problem:A VSCS is a set of regression models that contains the true model with a given level of *** the size of the VSCS properly reflects the model selection uncertainty,without specific assumptions on the true model,the VSCS is typically rather large(unless the num-ber of predictors is small).As a solution,we advocate special attention to the set of lower boundary models(LBMs),which are the most parsimonious models not statistically significantly inferior to the full model at a given confidence *** on the LBMs,variable importance and measures of co-appearance importance of predictors can be naturally defined.

关键词： Confidence set linear regression model selection variable selection

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Quantile Regression in the Secondary Analysis of Case-Control Data

Quantile Regression in the Secondary Analysis of Case-Contro...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Ying WEI Xiaoyu SONG Mengling Liu luliana IONITA-LAZA Joan REIBMAN Iuliana Ionita-Laza Department of Biostatistics Columbia UniversityNew YorkNY 10032 Heilbrunn Department of Population& Family Health Columbia UniversityNew YorkNY 10032 Department of Population Health New YorkUniversity School of MedicineNew YorkNY 10016 Department of Medicine New York University School of MedicineNew YorkNY 10016

Case-control design is widely used in epidemiology and other fields to identify factors associated with a *** collected from existing case-control studies can also provide a cost-effective way to investigate the association of risk factors with secondary *** the secondary outcome is a continuous random variable,most of the existing methods focus on the statistical inference on the mean of the secondary *** this article,we propose a quantile-based approach to facilitating a comprehensive investigation of covariates'effects on multiple quantiles of the secondary *** construct a new family of estimating equations combining observed and pseudo outcomes,which lead to consistent estimation of conditional quantiles using case-control *** are conducted to evaluate the performance of our proposed *** a case-control study on genetic association with asthma is used to demonstrate the *** materials for this article are available online.

关键词： Case-control studies Estimating equations GWAS Quantile regression Secondary phenotype

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Subgroup identification based on differential effect search-A recursive partitioning method for establishing response to treatment in patient subpopulations

Subgroup identification based on differential effect search-...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Ilya Lipkovich Alex Dmitrienko Jonathan Denne Gregory Enas Eli Lilly and Company IndianapolisINUSA

We propose a novel recursive partitioning method for identifying subgroups of subjects with enhanced treatment effects based on a differential effect search *** idea is to build a collection of subgroups by recursively partitioning a database into two subgroups at each parent group,such that the treatment effect within one of the two subgroups is maximized compared with the other *** process of data splitting continues until a predefined stopping condition has been *** method is similar to'interaction tree'approaches that allow incorporation of a treatment-by-split interaction in the splitting ***,unlike other tree-based methods,this method searches only within specific regions of the covariate space and generates multiple sub-groups of potential *** develop this method and provide guidance on key topics of interest that include generating multiple promising subgroups using different splitting criteria,choosing optimal values of complexity parameters via cross-validation,and addressing Type I error rate inflation inherent in data mining applications using a resampling-based *** evaluate the operating characteristics of the procedure using a simulation study and illustrate the method with a clinical trial example.

关键词： recursive partitioning data mining subgroup analysis in clinical trials

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Proper Analysis of Secondary Phenotype Data in Case-Control Association Studies

Proper Analysis of Secondary Phenotype Data in Case-Control ...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： D.Y.Lin D.Zeng Department of Biostatistics University of North CarolinaChapel HillNorth Carolina

Case-control association studies often collect extensive information on secondary phenotypes,which are quantitative or qualitative traits other than the case-control *** secondary phenotypes can yield valuable insights into biological pathways and identify genetic variants influencing phenotypes of direct *** publications on secondary phenotypes have used standard statistical methods,such as least-squares regression for quantitative *** of unequal selection probabilities between cases and controls,the case-control sample is not a random sample from the general *** a result,standard statistical analysis of secondary phenotype data can be extremely *** one may avoid the sampling bias by analyzing cases and controls separately or by including the case-control status as a covariate in the model,the associations between a secondary phenotype and a genetic variant in the case and control groups can be quite different from the association in the general *** this article,we present novel statistical methods that properly reflect the case-control sampling in the analysis of secondary phenotype *** new methods provide unbiased estimation of genetic effects and accurate control of false-positive rates while maximizing statistical *** demonstrate the pitfalls of the standard methods and the advantages of the new methods both analytically and *** relevant software is available at our website.

关键词： case-control sampling complex diseases genomewide association studies linear regression maximum likelihood meta-analysis quantitative traits secondary traits SNPs

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The design versus the analysis of observational studies for causal effects:Parallels with the design of randomized trials

The design versus the analysis of observational studies for ...

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2017第七届临床评价方法与应用国际研讨会暨生物统计国际研讨会

作者： Donald B.Rubin Department of Statistics Harvard University1 Oxford Street7th FloorCambridgeMA 02138U.S.A

For estimating causal effects of treatments,randomized experiments are generally considered the gold ***,they are often infeasible to conduct for a variety of reasons,such as ethical concerns,excessive expense,or ***,much of our knowledge of causal effects must come from non-randomized observational *** article will advocate the position that observational studies can and should be designed to approximate randomized experiments as closely as *** particular,observational studies should be designed using only background information to create subgroups of similar treated and control units,where'similar'here refers to their distributions of background *** great importance,this activity should be conducted without any access to any outcome data,thereby assuring the objectivity of the *** many situations,this objective creation of subgroups of similar treated and control units,which are balanced with respect to covariates,can be accomplished using propensity score *** theoretical perspective underlying this position will be presented followed by a particular application in the context of the US tobacco *** application uses propensity score methods to create subgroups of treated units(male current smokers)and control units(male never smokers)who are at least as similar with respect to their distributions of observed background characteristics as if they had been *** collection of these subgroups then'approximate'a randomized block experiment with respect to the observed *** 2006 John Wiley & Sons,Ltd.

关键词： assignment mechanism causal inference objective design propensity scores Rubin causal model tobacco litigation

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