Multiple Testing Problems in Pharmaceutical Statistics

Author:   Alex Dmitrienko ,  Ajit C. Tamhane ,  Frank Bretz ,  Frank Bretz (Novartis)
Publisher:   Taylor & Francis Inc
Volume:   v. 33
ISBN:  

9781584889847


Pages:   322
Publication Date:   08 December 2009
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Our Price $210.00 Quantity:  
Add to Cart

Share |

Multiple Testing Problems in Pharmaceutical Statistics


Overview

Full Product Details

Author:   Alex Dmitrienko ,  Ajit C. Tamhane ,  Frank Bretz ,  Frank Bretz (Novartis)
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Volume:   v. 33
Dimensions:   Width: 15.60cm , Height: 2.30cm , Length: 23.40cm
Weight:   0.589kg
ISBN:  

9781584889847


ISBN 10:   1584889845
Pages:   322
Publication Date:   08 December 2009
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Reviews

! The first part of the book is a cohesive exploration of the uses of methods of multiple hypothesis testing. These chapters are understandable for a reader who wants to study multiple testing methods beyond the post-hoc tests presented in a course on design of experiments. ! The final chapter provides an accessible description of problems in testing data from microarrays. --Biometrics, September 2010 If you are a statistician in the pharmaceutical industry looking for a comprehensive description of multiple testing in a clinical trial, this book is for you. Each of the main sources of multiplicity in clinical trials, such as several doses, endpoints, interim analyses etc., are discussed in detail. On the way, you will encounter dose-finding, adaptive designs and even microarray experiments. The book can undoubtedly be of value to wider groups -- in fact we would rank it as the best book on multiplicity given its up-to-date material ! the book certainly attains its objective of being a modern summary of the approaches to multiplicity issues primarily in clinical trials, serving as an excellent guide for those who find themselves face to face with simultaneous testing and would like to have an overview over possible ways of tackling the problem. ! --Vera Lisovskaja and Carl-Fredrik Burman, Journal of Biopharmaceutical Statistics, Issue 6, 2010


If you are a statistician in the pharmaceutical industry looking for a comprehensive description of multiple testing in a clinical trial, this book is for you. Each of the main sources of multiplicity in clinical trials, such as several doses, endpoints, interim analyses etc., are discussed in detail. On the way, you will encounter dose-finding, adaptive designs and even microarray experiments. The book can undoubtedly be of value to wider groups -- in fact we would rank it as the best book on multiplicity given its up-to-date material ! the book certainly attains its objective of being a modern summary of the approaches to multiplicity issues primarily in clinical trials, serving as an excellent guide for those who find themselves face to face with simultaneous testing and would like to have an overview over possible ways of tackling the problem. ! --Vera Lisovskaja and Carl-Fredrik Burman, Journal of Biopharmaceutical Statistics, Issue 6, 2010


This book is an important contribution to the increasing literature about multiple testing. The book focuses on pharmaceutical statistics with emphasis on clinical research. The methodology and applications described are nonetheless relevant to other fields. ! The book's strength lies in the completeness in the topics covered and the updated nature of material presented. Most of the recently developed methods are results of investigations by the book's authors, who are the leading scientists in the field. ! I find this book well structured and having fairly well-interconnected chapters. This work has been conceived to suit perfectly the bookshelf of a clinical statistician in the pharmaceutical sector and is a valuable resource and reference for statisticians who are interested in the subject. --Gonzalo Duran Pacheco and F. Hoffmann-La Roche, Journal of the Royal Statistical Society: Series A, Vol. 174, October 2011 The book presents the subject matter in a way that is very thorough and is written by some of the top researchers in the field. ! the book is a good one and libraries should be encouraged to purchase a copy. It will be useful to those researchers in both the biomedical and statistics fields. Practising statisticians in industry stand to benefit most from the book because of its completeness. --Isaac Dialsingh, Journal of Applied Statistics, 2011 ! The first part of the book is a cohesive exploration of the uses of methods of multiple hypothesis testing. These chapters are understandable for a reader who wants to study multiple testing methods beyond the post-hoc tests presented in a course on design of experiments. ! The final chapter provides an accessible description of problems in testing data from microarrays. --Biometrics, September 2010 If you are a statistician in the pharmaceutical industry looking for a comprehensive description of multiple testing in a clinical trial, this book is for you. Each of the main sources of multiplicity in clinical trials, such as several doses, endpoints, interim analyses etc., are discussed in detail. On the way, you will encounter dose-finding, adaptive designs and even microarray experiments. The book can undoubtedly be of value to wider groups -- in fact we would rank it as the best book on multiplicity given its up-to-date material ! the book certainly attains its objective of being a modern summary of the approaches to multiplicity issues primarily in clinical trials, serving as an excellent guide for those who find themselves face to face with simultaneous testing and would like to have an overview over possible ways of tackling the problem. ! --Vera Lisovskaja and Carl-Fredrik Burman, Journal of Biopharmaceutical Statistics, Issue 6, 2010


Author Information

Alex Dmitrienko is a research advisor in Global Statistical Sciences at Eli Lilly and Company in Indianapolis, Indiana. Ajit C. Tamhane is senior associate dean and professor of industrial engineering and management sciences in the McCormick School of Engineering and Applied Science at Northwestern University in Illinois. Frank Bretz is a biometrical fellow of clinical information sciences at Novartis Pharma AG in Switzerland. He is also an adjunct professor at Hannover Medical School in Germany.

Tab Content 6

Author Website:  

Countries Available

All regions
Latest Reading Guide

NOV RG 20252

 

Shopping Cart
Your cart is empty
Shopping cart
Mailing List