Confidence Intervals for Discrete Data in Clinical Research

Confidence Intervals for Discrete Data in Clinical Research
Author: Vivek Pradhan
Publisher: CRC Press
Total Pages: 240
Release: 2021-11-15
Genre: Mathematics
ISBN: 1351690175
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Confidence Intervals for Discrete Data in Clinical Research is designed as a toolbox for biomedical researchers. Analysis of discrete data is one of the most used yet vexing areas in clinical research. The array of methodologies available in the literature to address the inferential questions for binomial and multinomial data can be a double-edged sword. On the one hand, these methods open a rich avenue of exploration of data; on the other, the wide-ranging and competing methodologies potentially lead to conflicting inferences, adding to researchers' confusion and frustration and also leading to reporting bias. This book addresses the problems that many practitioners experience in choosing and implementing fit for purpose data analysis methods to answer critical inferential questions for binomial and count data. The book is an outgrowth of the authors' collective experience in biomedical research and provides an excellent overview of inferential questions of interest for binomial proportions and rates based on count data, and reviews various solutions to these problems available in the literature. Each chapter discusses the strengths and weaknesses of the methods and suggests practical recommendations. The book's primary focus is on applications in clinical research, and the goal is to provide direct benefit to the users involved in the biomedical field.

Confidence Intervals for Discrete Data in Clinical Research

Confidence Intervals for Discrete Data in Clinical Research
Author: Ashis Gangopadhyay
Publisher:
Total Pages: 0
Release: 2024-01-29
Genre: Mathematics
ISBN: 9781032128634
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There is only one published book on confidence interval for clinical research. This book has a cookbook style with several examples and codes so that methods presented in the book can be implemented. The primary audience will be statisticians.

Encyclopedia of Research Design

Encyclopedia of Research Design
Author: Neil J. Salkind
Publisher: SAGE
Total Pages: 1779
Release: 2010-06-22
Genre: Philosophy
ISBN: 1412961270
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"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

Statistical Thinking in Clinical Trials

Statistical Thinking in Clinical Trials
Author: Michael A. Proschan
Publisher: CRC Press
Total Pages: 270
Release: 2021-11-24
Genre: Mathematics
ISBN: 1351673114
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Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change. Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.

Hybrid Frequentist/Bayesian Power and Bayesian Power in Planning Clinical Trials

Hybrid Frequentist/Bayesian Power and Bayesian Power in Planning Clinical Trials
Author: Andrew P. Grieve
Publisher: CRC Press
Total Pages: 193
Release: 2022-06-19
Genre: Medical
ISBN: 1000590232
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Hybrid Frequentist/Bayesian Power and Bayesian Power in Planning Clinical Trials provides a practical introduction to unconditional approaches to planning randomised clinical trials, particularly aimed at drug development in the pharmaceutical industry. This book is aimed at providing guidance to practitioners in using average power, assurance and related concepts. This book brings together recent research and sets them in a consistent framework and provides a fresh insight into how such methods can be used. Features: A focus on normal theory linking average power, expected power, predictive power, assurance, conditional Bayesian power and Bayesian power. Extensions of the concepts to binomial, and time-to-event outcomes and non-inferiority trials An investigation into the upper bound on average power, assurance and Bayesian power based on the prior probability of a positive treatment effect Application of assurance to a series of trials in a development program and an introduction of the assurance of an individual trial conditional on the positive outcome of an earlier trial in the program, or to the successful outcome of an interim analysis Prior distribution of power and sample size Extension of the basic approach to proof-of-concept trials with dual success criteria Investigation of the connection between conditional and predictive power at an interim analysis and power and assurance Introduction of the idea of surety in sample sizing of clinical trials based on the width of the confidence intervals for the treatment effect, and an unconditional version.

Medical Statistics for Cancer Studies

Medical Statistics for Cancer Studies
Author: Trevor F. Cox
Publisher: CRC Press
Total Pages: 334
Release: 2022-06-23
Genre: Mathematics
ISBN: 1000601102
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Cancer is a dreaded disease. One in two people will be diagnosed with cancer within their lifetime. Medical Statistics for Cancer Studies shows how cancer data can be analysed in a variety of ways, covering cancer clinical trial data, epidemiological data, biological data, and genetic data. It gives some background in cancer biology and genetics, followed by detailed overviews of survival analysis, clinical trials, regression analysis, epidemiology, meta-analysis, biomarkers, and cancer informatics. It includes lots of examples using real data from the author’s many years of experience working in a cancer clinical trials unit. Features: A broad and accessible overview of statistical methods in cancer research Necessary background in cancer biology and genetics Details of statistical methodology with minimal algebra Many examples using real data from cancer clinical trials Appendix giving statistics revision.

Advanced Statistics in Regulatory Critical Clinical Initiatives

Advanced Statistics in Regulatory Critical Clinical Initiatives
Author: Wei Zhang
Publisher: CRC Press
Total Pages: 318
Release: 2022-05-25
Genre: Mathematics
ISBN: 1000567990
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Advanced Statistics in Regulatory Critical Clinical Initiatives is focused on the critical clinical initiatives introduced by the 21st Century Cure Act passed by the United States Congress in December 2016. The book covers everything from the outline of the initiatives to analysis on the effect on biopharmaceutical research and development. Advanced Statistics in Regulatory Critical Clinical Initiatives provides innovative ways to resolve common challenges in statistical research of rare diseases such small sample sizes and provides guidance for combined use of data. With analysis from regulatory and scientific perspectives this book is an ideal companion for researchers in biostatistics, pharmaceutical development, and policy makers in related fields. Key Features: Provides better understanding of innovative design and analysis of each critical clinical initiatives which may be used in regulatory review/approval of drug development. Makes recommendations to evaluate submissions accurately and reliably. Proposes innovative study designs and statistical methods for oncology and/or rare disease drug development. Provides insight regarding current regulatory guidance on drug development such as gene therapy and rare diseases.

Case Studies in Bayesian Methods for Biopharmaceutical CMC

Case Studies in Bayesian Methods for Biopharmaceutical CMC
Author: Paul Faya
Publisher: CRC Press
Total Pages: 354
Release: 2022-12-15
Genre: Mathematics
ISBN: 1000824772
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The subject of this book is applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies in the biopharmaceutical industry. The book has multiple authors from industry and academia, each contributing a case study (chapter). The collection of case studies covers a broad array of CMC topics, including stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and comparability studies. The analysis of each case study includes a presentation of code and reproducible output. This book is written with an academic level aimed at practicing nonclinical biostatisticians, most of whom have graduate degrees in statistics. • First book of its kind focusing strictly on CMC Bayesian case studies • Case studies with code and output • Representation from several companies across the industry as well as academia • Authors are leading and well-known Bayesian statisticians in the CMC field • Accompanying website with code for reproducibility • Reflective of real-life industry applications/problems

Efficacy Analysis in Clinical Trials an Update

Efficacy Analysis in Clinical Trials an Update
Author: Ton J. Cleophas
Publisher: Springer Nature
Total Pages: 304
Release: 2019-09-03
Genre: Medical
ISBN: 3030199185
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Machine learning and big data is hot. It is, however, virtually unused in clinical trials. This is so, because randomization is applied to even out multiple variables Modern medical computer files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are required This is the first publication of clinical trials that have been systematically analyzed with machine learning. In addition, all of the machine learning analyses were tested against traditional analyses. Step by step statistics for self-assessments are included The authors conclude, that machine learning is often more informative, and provides better sensitivities of testing than traditional analytic methods do

Digital Therapeutics

Digital Therapeutics
Author: Oleksandr Sverdlov
Publisher: CRC Press
Total Pages: 462
Release: 2022-12-06
Genre: Mathematics
ISBN: 1000799239
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One of the hallmarks of the 21st century medicine is the emergence of digital therapeutics (DTx)—evidence-based, clinically validated digital technologies to prevent, diagnose, treat, and manage various diseases and medical conditions. DTx solutions have been gaining interest from patients, investors, healthcare providers, health authorities, and other stakeholders because of the potential of DTx to deliver equitable, massively scalable, personalized and transformative treatments for different unmet medical needs. Digital Therapeutics: Scientific, Statistical, Clinical, and Regulatory Aspects is an unparalleled summary of the current scientific, statistical, developmental, and regulatory aspects of DTx which is poised to become the fastest growing area of the biopharmaceutical and digital medicine product development. This edited volume intends to provide a systematic exposition to digital therapeutics through 19 peer-reviewed chapters written by subject matter experts in this emerging field. This edited volume is an invaluable resource for business leaders and researchers working in public health, healthcare, digital health, information technology, and biopharmaceutical industries. It will be also useful for regulatory scientists involved in the review of DTx products, and for faculty and students involved in an interdisciplinary research on digital health and digital medicine. Key Features: Provides the taxonomy of the concepts and a navigation tool for the field of DTx. Covers important strategic aspects of the DTx industry, thereby helping investors, developers, and regulators gain a better appreciation of the potential value of DTx. Expounds on many existing and emerging state-of-the art scientific and technological tools, as well as data privacy, ethical and regulatory considerations for DTx product development. Presents several case studies of successful development of some of the most remarkable DTx products. Provides some perspectives and forward-looking statements on the future of digital medicine.