Analysis Of Clinical Trials Using Sas
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Author |
: Alex Dmitrienko |
Publisher |
: SAS Institute |
Total Pages |
: 455 |
Release |
: 2017-07-17 |
ISBN-10 |
: 9781635261448 |
ISBN-13 |
: 1635261449 |
Rating |
: 4/5 (48 Downloads) |
Synopsis Analysis of Clinical Trials Using SAS by : Alex Dmitrienko
Analysis of Clinical Trials Using SAS®: A Practical Guide, Second Edition bridges the gap between modern statistical methodology and real-world clinical trial applications. Tutorial material and step-by-step instructions illustrated with examples from actual trials serve to define relevant statistical approaches, describe their clinical trial applications, and implement the approaches rapidly and efficiently using the power of SAS. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials. Commonly used methods are covered, including dose-escalation and dose-finding methods that are applied in Phase I and Phase II clinical trials, as well as important trial designs and analysis strategies that are employed in Phase II and Phase III clinical trials, such as multiplicity adjustment, data monitoring, and methods for handling incomplete data. This book also features recommendations from clinical trial experts and a discussion of relevant regulatory guidelines. This new edition includes more examples and case studies, new approaches for addressing statistical problems, and the following new technological updates: SAS procedures used in group sequential trials (PROC SEQDESIGN and PROC SEQTEST) SAS procedures used in repeated measures analysis (PROC GLIMMIX and PROC GEE) macros for implementing a broad range of randomization-based methods in clinical trials, performing complex multiplicity adjustments, and investigating the design and analysis of early phase trials (Phase I dose-escalation trials and Phase II dose-finding trials) Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience and the ready-to-use SAS macros compiled in this book.
Author |
: Alex Dmitrienko |
Publisher |
: James Currey |
Total Pages |
: 0 |
Release |
: 2017 |
ISBN-10 |
: 162959847X |
ISBN-13 |
: 9781629598475 |
Rating |
: 4/5 (7X Downloads) |
Synopsis Analysis of Clinical Trials Using SAS by : Alex Dmitrienko
Includes bibliographical references and index.
Author |
: Ding-Geng (Din) Chen |
Publisher |
: CRC Press |
Total Pages |
: 385 |
Release |
: 2017-06-01 |
ISBN-10 |
: 9781351651141 |
ISBN-13 |
: 1351651145 |
Rating |
: 4/5 (41 Downloads) |
Synopsis Clinical Trial Data Analysis Using R and SAS by : Ding-Geng (Din) Chen
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.
Author |
: Sandeep Menon |
Publisher |
: SAS Institute |
Total Pages |
: 482 |
Release |
: 2015-12-09 |
ISBN-10 |
: 9781629600826 |
ISBN-13 |
: 1629600822 |
Rating |
: 4/5 (26 Downloads) |
Synopsis Modern Approaches to Clinical Trials Using SAS by : Sandeep Menon
Get the tools you need to use SAS® in clinical trial design! Unique and multifaceted, Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods, edited by Sandeep M. Menon and Richard C. Zink, thoroughly covers several domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods that are applicable to and widely used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, the book touches on a wide variety of topics, including dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs that incorporate historical data; adaptive sample size re-estimation; adaptive randomization to allocate subjects to more effective treatments; and population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology, and rheumatology. Individual chapters are authored by renowned contributors, experts, and key opinion leaders from the pharmaceutical/medical device industry or academia. Numerous real-world examples and sample SAS code enable users to readily apply novel clinical trial design and analysis methodologies in practice.
Author |
: Glenn Walker |
Publisher |
: SAS Institute |
Total Pages |
: 553 |
Release |
: 2010-02-15 |
ISBN-10 |
: 9781607644255 |
ISBN-13 |
: 1607644258 |
Rating |
: 4/5 (55 Downloads) |
Synopsis Common Statistical Methods for Clinical Research with SAS Examples, Third Edition by : Glenn Walker
Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data. Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is an applications book with minimal theory. Each section begins with an overview helpful to nonstatisticians and then drills down into details that will be valuable to statistical analysts and programmers. Further details, as well as bonus information and a guide to further reading, are presented in the extensive appendices. This text is a one-source guide for statisticians that documents the use of the tests used most often in clinical research, with assumptions, details, and some tricks--all in one place. This book is part of the SAS Press program.
Author |
: Carol I. Matthews |
Publisher |
: SAS Institute |
Total Pages |
: 229 |
Release |
: 2008 |
ISBN-10 |
: 9781599941288 |
ISBN-13 |
: 1599941287 |
Rating |
: 4/5 (88 Downloads) |
Synopsis Validating Clinical Trial Data Reporting with SAS by : Carol I. Matthews
This indispensable guide focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and output to the Food and Drug Administration.
Author |
: Alex Dmitrienko, Ph.D. |
Publisher |
: SAS Institute |
Total Pages |
: 464 |
Release |
: 2007-02-07 |
ISBN-10 |
: 9781629590301 |
ISBN-13 |
: 1629590304 |
Rating |
: 4/5 (01 Downloads) |
Synopsis Pharmaceutical Statistics Using SAS by : Alex Dmitrienko, Ph.D.
Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.
Author |
: Christophe Lalanne |
Publisher |
: Elsevier |
Total Pages |
: 176 |
Release |
: 2017-06-22 |
ISBN-10 |
: 9780081011713 |
ISBN-13 |
: 0081011717 |
Rating |
: 4/5 (13 Downloads) |
Synopsis Biostatistics and Computer-based Analysis of Health Data Using SAS by : Christophe Lalanne
This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands. - Presents the use of SAS software in the statistical approach for the management of data modeling - Includes elements of the language and descriptive statistics - Supplies measures of association, comparison of means, and proportions for two or more samples - Explores linear and logistic regression - Provides survival data analysis
Author |
: Sanjay Matange |
Publisher |
: SAS Institute |
Total Pages |
: 270 |
Release |
: 2016-03-21 |
ISBN-10 |
: 9781629602073 |
ISBN-13 |
: 1629602078 |
Rating |
: 4/5 (73 Downloads) |
Synopsis Clinical Graphs Using SAS by : Sanjay Matange
SAS users in the Health and Life Sciences industry need to create complex graphs to analyze biostatistics data and clinical data, and they need to submit drugs for approval to the FDA. Graphs used in the HLS industry are complex in nature and require innovative usage of the graphics features. Clinical Graphs Using SAS® provides the knowledge, the code, and real-world examples that enable you to create common clinical graphs using SAS graphics tools, such as the Statistical Graphics procedures and the Graph Template Language. This book describes detailed processes to create many commonly used graphs in the Health and Life Sciences industry. For SAS® 9.3 and SAS® 9.4 it covers many improvements in the graphics features that are supported by the Statistical Graphics procedures and the Graph Template Language, many of which are a direct result of the needs of the Health and Life Sciences community. With the addition of new features in SAS® 9.4, these graphs become positively easy to create. Topics covered include the usage of SGPLOT procedure, the SGPANEL procedure and the Graph Template Language for the creation of graphs like forest plots, swimmer plots, and survival plots.
Author |
: Kriss Harris |
Publisher |
: SAS Institute |
Total Pages |
: 198 |
Release |
: 2020-11-25 |
ISBN-10 |
: 9781952365973 |
ISBN-13 |
: 195236597X |
Rating |
: 4/5 (73 Downloads) |
Synopsis SAS Graphics for Clinical Trials by Example by : Kriss Harris
Create industry-compliant graphs with this practical guide for professionals Analysis of clinical trial results is easier when the data is presented in a visual form. However, clinical graphs must conform to specific guidelines in order to satisfy regulatory agency requirements. If you are a programmer working in the health care and life sciences industry and you want to create straightforward, visually appealing graphs using SAS, then this book is designed specifically for you. Written by two experienced practitioners, the book explains why certain graphs are requested, gives the necessary code to create the graphs, and shows you how to create graphs from ADaM data sets modeled on real-world CDISC pilot study data. SAS Graphics for Clinical Trials by Example demonstrates step-by-step how to create both simple and complex graphs using Graph Template Language (GTL) and statistical graphics procedures, including the SGPLOT and SGPANEL procedures. You will learn how to generate commonly used plots such as Kaplan-Meier plots and multi-cell survival plots as well as special purpose graphs such as Venn diagrams and interactive graphs. Because your graph is only as good as the aesthetic appearance of the output, you will learn how to create a custom style, change attributes, and set output options. Whether you are just learning how to produce graphs or have been working with graphs for a while, this book is a must-have resource to solve even the most challenging clinical graph problems.