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Analyzing Longitudinal Clinical Trial Data
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Book Synopsis Analyzing Longitudinal Clinical Trial Data by : Craig Mallinckrodt
Download or read book Analyzing Longitudinal Clinical Trial Data written by Craig Mallinckrodt and published by CRC Press. This book was released on 2016-12-12 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Analysis of Longitudinal Data by : Peter Diggle
Download or read book Analysis of Longitudinal Data written by Peter Diggle and published by Oxford University Press, USA. This book was released on 2013-03-14 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.
Book Synopsis Preventing and Treating Missing Data in Longitudinal Clinical Trials by : Craig H. Mallinckrodt
Download or read book Preventing and Treating Missing Data in Longitudinal Clinical Trials written by Craig H. Mallinckrodt and published by Cambridge University Press. This book was released on 2013-01-28 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on the prevention and treatment of missing data in longitudinal clinical trials, looking at key principles and explaining analytic methods.
Book Synopsis Methods and Applications of Longitudinal Data Analysis by : Xian Liu
Download or read book Methods and Applications of Longitudinal Data Analysis written by Xian Liu and published by Elsevier. This book was released on 2015-09-11 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: descriptive methods for delineating trends over time linear mixed regression models with both fixed and random effects covariance pattern models on correlated errors generalized estimating equations nonlinear regression models for categorical repeated measurements techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.
Book Synopsis Clinical Trial Data Analysis Using R by : Ding-Geng (Din) Chen
Download or read book Clinical Trial Data Analysis Using R written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2010-12-14 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Analysis Using R provides a thorough presentation of biostatistical analyses of clinical trial data and shows step by step how to implement the statistical methods using R. The book’s practical, detailed approach draws on the authors’ 30 years of real-world experience in biostatistical research and clinical development. Each chapter presents examples of clinical trials based on the authors’ actual experiences in clinical drug development. Various biostatistical methods for analyzing the data are then identified. The authors develop analysis code step by step using appropriate R packages and functions. This approach enables readers to gain an understanding of the analysis methods and R implementation so that they can use R to analyze their own clinical trial data. With step-by-step illustrations of R implementations, this book shows how to easily use R to simulate and analyze data from a clinical trial. It describes numerous up-to-date statistical methods and offers sound guidance on the processes involved in clinical trials.
Book Synopsis Longitudinal Data Analysis by : Garrett Fitzmaurice
Download or read book Longitudinal Data Analysis written by Garrett Fitzmaurice and published by CRC Press. This book was released on 2008-08-11 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Book Synopsis Clinical Trial Data Analysis Using R and SAS by : Ding-Geng (Din) Chen
Download or read book Clinical Trial Data Analysis Using R and SAS written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2017-06-01 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."—Journal of Statistical Software Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book’s practical, detailed approach draws on the authors’ 30 years’ experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What’s New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.
Book Synopsis Clinical Trial Data Analysis Using R and SAS by : Ding-Geng (Din) Chen
Download or read book Clinical Trial Data Analysis Using R and SAS written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2017-06-01 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."—Journal of Statistical Software Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book’s practical, detailed approach draws on the authors’ 30 years’ experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What’s New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.
Book Synopsis Small Clinical Trials by : Institute of Medicine
Download or read book Small Clinical Trials written by Institute of Medicine and published by National Academies Press. This book was released on 2001-01-01 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
Book Synopsis Clinical Statistics: Introducing Clinical Trials, Survival Analysis, and Longitudinal Data Analysis by : Olga Korosteleva
Download or read book Clinical Statistics: Introducing Clinical Trials, Survival Analysis, and Longitudinal Data Analysis written by Olga Korosteleva and published by Jones & Bartlett Learning. This book was released on 2009 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical Statistics: Introducing Clinical Trials, Survival Analysis, and Longitudinal Data Analysis provides the mathematic background necessary for students preparing for a career as a statistician in the biomedical field. The manual explains the steps a clinical statistician must take in clinical trials from protocol writing to subject randomization, to data monitoring, and on to writing a final report to the FDA. All of the necessary fundamentals of statistical analysis: survival and longitudinal data analysis are included. SAS procedures are explained with simple examples and the mathematics behind these SAS procedures are covered in detail with the statistical software program SAS which is implemented throughout the text. Complete codes are given for every example found in the text. The exercises featured throughout the guide are both theoretical and applied making it appropriate for those moving on to different clinical settings. Students will find Clinical Statistics to be a handy lab reference for coursework and in their future careers.
Book Synopsis A mixed model approach for intent-to-treat analysis in longitudinal clinical trials with missing values by : Hrishikesh Chakraborty
Download or read book A mixed model approach for intent-to-treat analysis in longitudinal clinical trials with missing values written by Hrishikesh Chakraborty and published by RTI Press. This book was released on 2009-02-28 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing values and dropouts are common issues in longitudinal studies in all areas of medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted method for the analysis of controlled clinical trials. In most controlled clinical trials, some patients do not complete their intended followup according to the protocol for a variety of reasons; this problem generates missing values. Missing values lead to concern and confusion in identifying the ITT population, which makes the data analysis more complex and challenging. No adequate strategy exists for ITT analyses of longitudinal controlled clinical trial data with missing values. Several ad hoc strategies for dealing with missing values for an ITT analysis are common in the practice of controlled clinical trials. We performed a detailed investigation based on simulation studies to develop recommendations for this situation. We compared sizes (type I errors) and power between some popular ad hoc approaches and the linear mixed model approach under different missing value scenarios. Our results suggest that, for studies with a high percentage of missing values, the mixed model approach without any ad hoc imputation is more powerful than other options.
Book Synopsis Missing Data in Longitudinal Studies by : Michael J. Daniels
Download or read book Missing Data in Longitudinal Studies written by Michael J. Daniels and published by CRC Press. This book was released on 2008-03-11 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To illustrate these methods, the authors employ
Book Synopsis Sharing Clinical Trial Data by : Institute of Medicine
Download or read book Sharing Clinical Trial Data written by Institute of Medicine and published by National Academies Press. This book was released on 2015-04-20 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research--from funders, to researchers, to journals, to physicians, and ultimately, to patients.
Book Synopsis Applied Longitudinal Data Analysis for Epidemiology by : Jos W. R. Twisk
Download or read book Applied Longitudinal Data Analysis for Epidemiology written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2013-05-09 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.
Book Synopsis Estimands, Estimators and Sensitivity Analysis in Clinical Trials by : Craig Mallinckrodt
Download or read book Estimands, Estimators and Sensitivity Analysis in Clinical Trials written by Craig Mallinckrodt and published by CRC Press. This book was released on 2019-12-23 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language, providing technical details, real-world examples, and SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence. This book lays out a path toward bridging some of these gaps. It offers A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1) Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs: A perspective on the role of the intention-to-treat principle Examples and case studies from various areas Example code in SAS and R A connection with causal inference Implications and methods for analysis of longitudinal trials with missing data Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.
Book Synopsis Preventing and Treating Missing Data in Longitudinal Clinical Trials by : Craig H. Mallinckrodt
Download or read book Preventing and Treating Missing Data in Longitudinal Clinical Trials written by Craig H. Mallinckrodt and published by Cambridge University Press. This book was released on 2013-01-28 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.
Book Synopsis Analyzing Longitudinal Clinical Trial Data by : Craig Mallinckrodt
Download or read book Analyzing Longitudinal Clinical Trial Data written by Craig Mallinckrodt and published by CRC Press. This book was released on 2016-12-12 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing Longitudinal Clinical Trial Data: A Practical Guide provide practical and easy to implement approaches for bringing the latest theory on analysis of longitudinal clinical trial data into routine practice.?This 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.
