Multiple Testing Problems in Pharmaceutical Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Testing Problems in Pharmaceutical Statistics write by Alex Dmitrienko. This book was released on 2009-12-08. Multiple Testing Problems in Pharmaceutical Statistics available in PDF, EPUB and Kindle. Useful Statistical Approaches for Addressing Multiplicity IssuesIncludes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple c
Clinical Trial Biostatistics and Biopharmaceutical Applications
Clinical Trial Biostatistics and Biopharmaceutical Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Clinical Trial Biostatistics and Biopharmaceutical Applications write by Walter R. Young. This book was released on 2014-11-20. Clinical Trial Biostatistics and Biopharmaceutical Applications available in PDF, EPUB and Kindle. Since 1945, "The Annual Deming Conference on Applied Statistics" has been an important event in the statistics profession. In Clinical Trial Biostatistics and Biopharmaceutical Applications, prominent speakers from past Deming conferences present novel biostatistical methodologies in clinical trials as well as up-to-date biostatistical applications from the pharmaceutical industry. Divided into five sections, the book begins with emerging issues in clinical trial design and analysis, including the roles of modeling and simulation, the pros and cons of randomization procedures, the design of Phase II dose-ranging trials, thorough QT/QTc clinical trials, and assay sensitivity and the constancy assumption in noninferiority trials. The second section examines adaptive designs in drug development, discusses the consequences of group-sequential and adaptive designs, and illustrates group sequential design in R. The third section focuses on oncology clinical trials, covering competing risks, escalation with overdose control (EWOC) dose finding, and interval-censored time-to-event data. In the fourth section, the book describes multiple test problems with applications to adaptive designs, graphical approaches to multiple testing, the estimation of simultaneous confidence intervals for multiple comparisons, and weighted parametric multiple testing methods. The final section discusses the statistical analysis of biomarkers from omics technologies, biomarker strategies applicable to clinical development, and the statistical evaluation of surrogate endpoints. This book clarifies important issues when designing and analyzing clinical trials, including several misunderstood and unresolved challenges. It will help readers choose the right method for their biostatistical application. Each chapter is self-contained with references.
Multiple Comparisons Using R
Multiple Comparisons Using R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Comparisons Using R write by Frank Bretz. This book was released on 2016-04-19. Multiple Comparisons Using R available in PDF, EPUB and Kindle. Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org After giving examples of multiplicity problems, the book covers general concepts and basic multiple comparisons procedures, including the Bonferroni method and Simes’ test. It then shows how to perform parametric multiple comparisons in standard linear models and general parametric models. It also introduces the multcomp package in R, which offers a convenient interface to perform multiple comparisons in a general context. Following this theoretical framework, the book explores applications involving the Dunnett test, Tukey’s all pairwise comparisons, and general multiple contrast tests for standard regression models, mixed-effects models, and parametric survival models. The last chapter reviews other multiple comparison procedures, such as resampling-based procedures, methods for group sequential or adaptive designs, and the combination of multiple comparison procedures with modeling techniques. Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. A self-contained introduction to multiple comparison procedures, this book offers strategies for constructing the procedures and illustrates the framework for multiple hypotheses testing in general parametric models. It is suitable for readers with R experience but limited knowledge of multiple comparison procedures and vice versa. See Dr. Bretz discuss the book.
Pharmaceutical Statistics Using SAS
Pharmaceutical Statistics Using SAS - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Pharmaceutical Statistics Using SAS write by Alex Dmitrienko, Ph.D.. This book was released on 2007-02-07. Pharmaceutical Statistics Using SAS available in PDF, EPUB and Kindle. Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.
Statistical Methods for Large-scale Multiple Testing Problems
Statistical Methods for Large-scale Multiple Testing Problems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Methods for Large-scale Multiple Testing Problems write by Yu Gao. This book was released on 2019. Statistical Methods for Large-scale Multiple Testing Problems available in PDF, EPUB and Kindle. A large-scale multiple testing problem simultaneously tests thousands or even millions of null hypotheses, and it is widely used in different fields, for example genetics and astronomy. An error rate serves as a measure of the performance of a testing procedure. The use of the family-wise error rate can accommodate any dependence between hypotheses, but it is often overly conservative and has limited detection power.The false discovery rate is more powerful, however not as widely used due to the requirement of independence and other reasons. In this thesis, we develop statistical methods for large-scale multiple testing problems in pharmacovigilance and genetic studies, and adopt the false discovery rate to improve the detection power by tacking mixed challenges.
