Sample Size Calculations For Clustered And Longitudinal Outcomes In Clinical Research
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Sample Size Calculations For Clustered And Longitudinal Outcomes In Clinical Research
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Author : Chul Ahn
language : en
Publisher: CRC Press
Release Date : 2014-12-09
Sample Size Calculations For Clustered And Longitudinal Outcomes In Clinical Research written by Chul Ahn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-09 with Mathematics categories.
This book explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies. For clustered studies, the authors provide sample size formulas that account for variable cluster sizes and within-cluster correlation. For longitudinal studies, they present sample size formulas that account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering, the authors describe how randomization impacts trial administration, analysis, and sample size requirement.
Sample Size Calculations For Clustered And Longitudinal Outcomes In Clinical Research
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Author : Chul Ahn
language : en
Publisher: CRC Press
Release Date : 2014-12-09
Sample Size Calculations For Clustered And Longitudinal Outcomes In Clinical Research written by Chul Ahn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-09 with Mathematics categories.
Accurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental treatments caused by an overpowered study. Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies. The book focuses on issues specific to the two types of correlated outcomes: longitudinal and clustered. For clustered studies, the authors provide sample size formulas that accommodate variable cluster sizes and within-cluster correlation. For longitudinal studies, they present sample size formulas to account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering, the level at which to perform randomization actually becomes a design parameter. The authors show how this can greatly impact trial administration, analysis, and sample size requirement. Addressing the overarching theme of sample size determination for correlated outcomes, this book provides a useful resource for biostatisticians, clinical investigators, epidemiologists, and social scientists whose research involves trials with correlated outcomes. Each chapter is self-contained so readers can explore topics relevant to their research projects without having to refer to other chapters.
Textbook Of Clinical Trials In Oncology
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Author : Susan Halabi
language : en
Publisher: CRC Press
Release Date : 2019-04-24
Textbook Of Clinical Trials In Oncology written by Susan Halabi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-24 with Mathematics categories.
There is an increasing need for educational resources for statisticians and investigators. Reflecting this, the goal of this book is to provide readers with a sound foundation in the statistical design, conduct, and analysis of clinical trials. Furthermore, it is intended as a guide for statisticians and investigators with minimal clinical trial experience who are interested in pursuing a career in this area. The advancement in genetic and molecular technologies have revolutionized drug development. In recent years, clinical trials have become increasingly sophisticated as they incorporate genomic studies, and efficient designs (such as basket and umbrella trials) have permeated the field. This book offers the requisite background and expert guidance for the innovative statistical design and analysis of clinical trials in oncology. Key Features: Cutting-edge topics with appropriate technical background Built around case studies which give the work a "hands-on" approach Real examples of flaws in previously reported clinical trials and how to avoid them Access to statistical code on the book’s website Chapters written by internationally recognized statisticians from academia and pharmaceutical companies Carefully edited to ensure consistency in style, level, and approach Topics covered include innovating phase I and II designs, trials in immune-oncology and rare diseases, among many others
Design And Analysis Of Pragmatic Trials
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Author : Song Zhang
language : en
Publisher: CRC Press
Release Date : 2023-05-16
Design And Analysis Of Pragmatic Trials written by Song Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-16 with Mathematics categories.
This book begins with an introduction of pragmatic cluster randomized trials (PCTs) and reviews various pragmatic issues that need to be addressed by statisticians at the design stage. It discusses the advantages and disadvantages of each type of PCT, and provides sample size formulas, sensitivity analyses, and examples for sample size calculation. The generalized estimating equation (GEE) method will be employed to derive sample size formulas for various types of outcomes from the exponential family, including continuous, binary, and count variables. Experimental designs that have been frequently employed in PCTs will be discussed, including cluster randomized designs, matched-pair cluster randomized design, stratified cluster randomized design, stepped-wedge cluster randomized design, longitudinal cluster randomized design, and crossover cluster randomized design. It demonstrates that the GEE approach is flexible to accommodate pragmatic issues such as hierarchical correlation structures, different missing data patterns, randomly varying cluster sizes, etc. It has been reported that the GEE approach leads to under-estimated variance with limited numbers of clusters. The remedy for this limitation is investigated for the design of PCTs. This book can assist practitioners in the design of PCTs by providing a description of the advantages and disadvantages of various PCTs and sample size formulas that address various pragmatic issues, facilitating the proper implementation of PCTs to improve health care. It can also serve as a textbook for biostatistics students at the graduate level to enhance their knowledge or skill in clinical trial design. Key Features: Discuss the advantages and disadvantages of each type of PCTs, and provide sample size formulas, sensitivity analyses, and examples. Address an unmet need for guidance books on sample size calculations for PCTs; A wide variety of experimental designs adopted by PCTs are covered; The sample size solutions can be readily implemented due to the accommodation of common pragmatic issues encountered in real-world practice; Useful to both academic and industrial biostatisticians involved in clinical trial design; Can be used as a textbook for graduate students majoring in statistics and biostatistics.
Cluster Randomised Trials
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Author : Richard J. Hayes
language : en
Publisher: CRC Press
Release Date : 2017-07-06
Cluster Randomised Trials written by Richard J. Hayes and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Mathematics categories.
Cluster Randomised Trials, Second Edition discusses the design, conduct, and analysis of trials that randomise groups of individuals to different treatments. It explores the advantages of cluster randomisation, with special attention given to evaluating the effects of interventions against infectious diseases. Avoiding unnecessary mathematical detail, the book covers basic concepts underlying the use of cluster randomisation, such as direct, indirect, and total effects. In the time since the publication of the first edition, the use of cluster randomised trials (CRTs) has increased substantially, which is reflected in the updates to this edition. There are greatly expanded sections on randomisation, sample size estimation, and alternative designs, including new material on stepped wedge designs. There is a new section on handling ordinal outcome data, and an appendix with descriptions and/or generating code of the example data sets. Although the book mainly focuses on medical and public health applications, it shows that the rigorous evidence of intervention effects provided by CRTs has the potential to inform public policy in a wide range of other areas. The book encourages readers to apply the methods to their own trials, reproduce the analyses presented, and explore alternative approaches.
Power And Sample Size In R
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Author : Catherine M. Crespi
language : en
Publisher: CRC Press
Release Date : 2025-02-06
Power And Sample Size In R written by Catherine M. Crespi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-06 with Mathematics categories.
Power and Sample Size in R guides the reader through power and sample size calculations for a wide variety of study outcomes and designs and illustrates their implementation in R software. It is designed to be used as a learning tool for students as well as a resource for experienced statisticians and investigators. The book begins by explaining the process of power calculation step by step at an introductory level and then builds to increasingly complex and varied topics. For each type of study design, the information needed to perform a calculation and the factors that affect power are explained. Concepts are explained with statistical rigor but made accessible through intuition and examples. Practical advice for performing sample size and power calculations for real studies is given throughout. The book demonstrates calculations in R. It is integrated with the companion R package powertools and also draws on and summarizes the capabilities of other R packages. Only a basic proficiency in R is assumed. Topics include comparison of group means and proportions; ANOVA, including multiple comparisons; power for confidence intervals; multistage designs; linear, logistic and Poisson regression; crossover studies; multicenter, cluster randomized and stepped wedge designs; and time to event outcomes. Chapters are also devoted to designing noninferiority, superiority by a margin and equivalence studies and handling multiple primary endpoints. By emphasizing statistical thinking about the factors that influence power for different study designs and outcomes as well as providing R code, this book equips the reader with the knowledge and tools to perform their own calculations with confidence. Key Features: Explains power and sample size calculation for a wide variety of study designs and outcomes Suitable for both students and experienced researchers Highlights key factors influencing power and provides practical tips for designing real studies Includes extensive examples with R code
Statistical Topics In Health Economics And Outcomes Research
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Author : Demissie Alemayehu
language : en
Publisher: CRC Press
Release Date : 2017-11-22
Statistical Topics In Health Economics And Outcomes Research written by Demissie Alemayehu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Mathematics categories.
With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.
Analyzing Longitudinal Clinical Trial Data
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Author : Craig Mallinckrodt
language : en
Publisher: CRC Press
Release Date : 2016-12-12
Analyzing Longitudinal Clinical Trial Data written by Craig Mallinckrodt and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-12 with Mathematics categories.
Analyzing Longitudinal Clinical Trial Data: A Practical Guide provides practical and easy to implement approaches for bringing the latest theory on analysis of longitudinal clinical trial data into routine practice.The book, with its example-oriented approach that includes numerous SAS and R code fragments, is an essential resource for statisticians and graduate students specializing in medical research. The authors provide clear descriptions of the relevant statistical theory and illustrate practical considerations for modeling longitudinal data. Topics covered include choice of endpoint and statistical test; modeling means and the correlations between repeated measurements; accounting for covariates; modeling categorical data; model verification; methods for incomplete (missing) data that includes the latest developments in sensitivity analyses, along with approaches for and issues in choosing estimands; and means for preventing missing data. Each chapter stands alone in its coverage of a topic. The concluding chapters provide detailed advice on how to integrate these independent topics into an over-arching study development process and statistical analysis plan.
Multiregional Clinical Trials For Simultaneous Global New Drug Development
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Author : Joshua Chen
language : en
Publisher: CRC Press
Release Date : 2016-04-21
Multiregional Clinical Trials For Simultaneous Global New Drug Development written by Joshua Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-21 with Mathematics categories.
In a global clinical development strategy, multiregional clinical trials (MRCTs) are vital in the development of innovative medicines. Multiregional Clinical Trials for Simultaneous Global New Drug Development presents a comprehensive overview on the current status of conducting MRCTs in clinical development. International experts from academia, in
Modern Adaptive Randomized Clinical Trials
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Author : Oleksandr Sverdlov
language : en
Publisher: CRC Press
Release Date : 2015-06-30
Modern Adaptive Randomized Clinical Trials written by Oleksandr Sverdlov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-30 with Mathematics categories.
Is adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials? What kind of statistical inference should be used to achieve valid and unbiased treatment comparisons following adaptive random