Modern Clinical Trial Analysis: Applied Bioinformatics and Biostatistics in Cancer Research
Editat de Wan Tang, Xin Tuen Limba Engleză Paperback – 15 oct 2014
The coverage of these topics provides a quick introduction to these important statistical issues and methods for addressing them. As with the classic topics, this part of the volume on modern topics will enable researchers to grasp the statistical methods for addressing these emerging issues underlying modern clinical trials and to apply them to their research studies.
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Specificații
ISBN-13: 9781489987785
ISBN-10: 1489987789
Pagini: 264
Ilustrații: X, 254 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.37 kg
Ediția:2013
Editura: Springer
Colecția Springer
Seria Applied Bioinformatics and Biostatistics in Cancer Research
Locul publicării:New York, NY, United States
ISBN-10: 1489987789
Pagini: 264
Ilustrații: X, 254 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.37 kg
Ediția:2013
Editura: Springer
Colecția Springer
Seria Applied Bioinformatics and Biostatistics in Cancer Research
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Preface.- Survival Analysis.- Longitudinal Data Analysis.- Assessment of Diagnostic Tests and Instruments.- Analysis of Sequential Clinical Trials.- Dynamic Treatment Regimes.- Statistical Issues with Trial Data and Economic Modeling for Cost-effectiveness Evaluation.- Active-controlled Clinical Trials.- Thorough QT/QTc Clinical Trials .- Causal Inference in Cancer Clinical Trials.- Index.
Textul de pe ultima copertă
This volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. Starting with survival data analysis, this book transitions from such a classic topic to modern issues by stepping through diagnostic test and instrument assessment, sequential and dynamic treatment regimen, cost-effectiveness evaluation, equivalence testing. As some type of cancer such as the effect of smoking on lung cancer cannot be studied using randomized trials, a chapter on analysis of non-randomized studies is also included. The book concludes with a chapter discussing the opportunities and challenges that lie ahead in developing on person-centered treatment regimens.
The book provides an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out the analyses. Medical researchers with some background in clinical trial design and regression analysis as well as biostatisticians will find this book informative and helpful.
The book provides an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out the analyses. Medical researchers with some background in clinical trial design and regression analysis as well as biostatisticians will find this book informative and helpful.
Caracteristici
Discusses cutting-edge topics Provides analysis of data from dynamic treatment regimen study design, cost-effectiveness analysis, analysis of genomic data, and causal inference to Addresses confounding issues such as concurrent medication use and mechanism of action using marginal structural and structural equation models. Includes supplementary material: sn.pub/extras