Understanding Clinical Data Analysis


Understanding Clinical Data Analysis
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Understanding Clinical Data Analysis


Understanding Clinical Data Analysis
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Author : Ton J. Cleophas
language : en
Publisher: Springer
Release Date : 2016-08-23

Understanding Clinical Data Analysis written by Ton J. Cleophas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-23 with Medical categories.


This textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings. In the past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs.



Clinical Trial Data Analysis Using R


Clinical Trial Data Analysis Using R
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Author : Ding-Geng (Din) Chen
language : en
Publisher: CRC Press
Release Date : 2010-12-14

Clinical Trial Data Analysis Using R written by Ding-Geng (Din) 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 2010-12-14 with Mathematics categories.


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.



Understanding Clinical Research


Understanding Clinical Research
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Author : Kathryn Biddle
language : en
Publisher: Scion Publishing Ltd
Release Date : 2023-05-17

Understanding Clinical Research written by Kathryn Biddle and has been published by Scion Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-17 with Medical categories.


It is important for healthcare professionals to understand the basics of clinical research. This book offers a thorough explanation of the principles of clinical research, alongside a wide range of worked examples which show how these principles are applied in practice. Understanding Clinical Research takes readers from how to develop research questions, through the design of research studies, to disseminating research findings. Ethical considerations, research integrity, patient involvement, and study funding are all covered, along with an introduction to the key statistical methods needed for data analysis. Ideal for any healthcare professional: interested in understanding more about the development of evidence-based practice wanting to undertake research but not sure where to start considering or just starting a PhD / MD, or a PGCert in Research Studies



Understanding Clinical Research


Understanding Clinical Research
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Author : Renato D. Lopes
language : en
Publisher: McGraw Hill Professional
Release Date : 2013-05-22

Understanding Clinical Research written by Renato D. Lopes and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-22 with Medical categories.


A complete guide to understanding and applying clinical research results Ideal for both researchers and healthcare providers Understanding Clinical Research addresses both the operational challenges of clinical trials and the needs of clinicians to comprehend the nuances of research methods to accurately analyze study results. This timely resource covers all aspects of clinical trials--from study design and statistics to regulatory oversight--and it delivers a detailed yet streamlined overview of must-know research topics. The text features an accessible three-part organization that traces the evolution of clinical research and explains the bedrock principles and unique challenges of clinical experimentation and observational research. Reinforcing this content are real-life case examples--drawn from the authors' broad experience--that put chapter concepts into action and contribute to a working knowledge of integral research techniques. FEATURES: The most definitive guide to promoting excellence in clinical research, designed to empower healthcare providers to assess a study's strengths and weaknesses with confidence and apply this knowledge to optimize patient outcomes In-depth coverage of fundamental research methods and protocols from preeminent authorities provides readers with an instructive primer and a springboard for ongoing clinical research education Clear, comprehensive three-part organization: Section One: Evolution of Clinical Research offers a succinct history of clinical trials, drug regulations, and the role of the FDA while covering the impact of information technology and academic research organizations Section Two: Principles of Clinical Experimentation takes you through the typical phases of clinical trials in the development of medical products, from initial human subject research to postapproval surveillance studies Section Three: Observational Research highlights the underlying principles, pitfalls, and methods for case-control studies, cohort studies, registries, and subgroup analyses within randomized trials



Clinical Trial Data Analysis Using R And Sas


Clinical Trial Data Analysis Using R And Sas
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Author : Ding-Geng (Din) Chen
language : en
Publisher: CRC Press
Release Date : 2017-06-01

Clinical Trial Data Analysis Using R And Sas written by Ding-Geng (Din) 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 2017-06-01 with Mathematics categories.


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.



Understanding Clinical Papers


Understanding Clinical Papers
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Author : David Bowers
language : en
Publisher: John Wiley & Sons
Release Date : 2021-03-08

Understanding Clinical Papers written by David Bowers and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-08 with Medical categories.


For two decades, Understanding Clinical Papers has been helping students and professionals understand the research that supports evidence-based practice. Now in its fourth edition, this popular introductory textbook covers every major aspect of reading and evaluating clinical research literature, from identifying the aims and objectives of a paper to analysing the data with different multivariable methods. Numerous excerpts from actual clinical research papers make learning real and immediate, supported by a unique visual approach that reinforces key points and connects examples with the chapter material. The fourth edition includes extensively revised content throughout, including four brand-new chapters covering qualitative studies, Poisson regression, studies of complex interventions, and research using previously collected data. New and updated material discusses the difference between clinical and statistical significance, the consequences of multiple testing and methods of correction, how topic guides are used to explore and explain participants' experiences, standardised guidelines for writing trials and reviews, and much more. Offering clear explanations of important research-related topics, this reader-friendly resource: Offers a clear, concise, and accessible approach to learning how to read and analyse clinical research literature Features new coverage of qualitative research, including descriptive studies, sampling and populations, and identifying, summarising, and measuring qualitative characteristics Provides new material on missing data, sub-group analysis, feasibility and pilot studies, cluster randomised trials, and adaptive trial designs Includes new tables, abstracts, and excerpts from recent clinical research literature Understanding Clinical Papers is essential reading for all healthcare professionals and students, particularly those involved in clinical work and medical research, as well as general readers wanting to improve their understanding of research literature.



Fast Facts Medical Statistics


Fast Facts Medical Statistics
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Author : R. Kay
language : en
Publisher: Karger Medical and Scientific Publishers
Release Date : 2020-07-17

Fast Facts Medical Statistics written by R. Kay and has been published by Karger Medical and Scientific Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-17 with Medical categories.


Using real examples from oncology trials, but keeping it simple, this concise resource explains the basic principles of medical statistics so that you can better appraise clinical trial results. Key concepts covered in this book include: • hypothesis testing • Kaplan–Meier curves and other graphic representations of data • calculating the power of a study • the stopping rules for efficacy and futility. ' Fast Facts: Medical Statistics' is aimed at all clinicians, clinical scientists, medical writers and regulatory personnel who need a better understanding of the statistical terms and methods used in the planning of studies and the analysis of clinical trial data. If you have ever wanted to know what a type I error is, how an odds ratio is calculated or what a forest plot is really all about, then this is the book for you. Contents: • Statistical inference • Analysis of time-to-event endpoints • Power and sample size • Multiplicity • Interim analysis • Modeling • Graphical methods



Clinical Trial Data Analysis Using R And Sas


Clinical Trial Data Analysis Using R And Sas
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Author : Ding-Geng Chen
language : en
Publisher: CRC Press
Release Date : 2020-12-18

Clinical Trial Data Analysis Using R And Sas written by Ding-Geng 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 2020-12-18 with categories.


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.



Medical Statistics


Medical Statistics
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Author : Belinda Barton
language : en
Publisher: John Wiley & Sons
Release Date : 2014-10-06

Medical Statistics written by Belinda Barton and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-06 with Medical categories.


Medical Statistics provides the necessary statistical tools to enable researchers to undertake and understand evidence-based clinical research. It is a practical guide to conducting statistical research and interpreting statistics in the context of how the participants were recruited, how the study was designed, what types of variables were used, what effect size was found, and what the P values mean. It guides researchers through the process of selecting the correct statistics and show how to best report results for presentation and publication. Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors’ popular medical statistics courses. The table of contents is divided into sections according to whether data are continuous or categorical in nature as this distinction is fundamental to selecting the correct statistics. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. The chapters conclude with critical appraisal guidelines to help researchers review the reporting of results from each type of statistical test. This new edition includes a new chapter on repeated measures and mixed models and a helpful glossary of terms provides an easy reference that applies to all chapters.



Small Clinical Trials


Small Clinical Trials
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Author : Institute of Medicine
language : en
Publisher: National Academies Press
Release Date : 2001-01-01

Small Clinical Trials written by Institute of Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-01-01 with Medical categories.


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.