Common Statistical Methods For Clinical Research With Sas Examples

Author : Glenn Walker,Jack Shostak
Publisher : SAS Institute
Page : 553 pages
File Size : 52,9 Mb
Release : 2010-02-15
Category : Mathematics
ISBN : 9781607644255

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Common Statistical Methods for Clinical Research with SAS Examples, Third Edition by Glenn Walker,Jack Shostak Pdf

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 : Glenn Walker,Jack Shostak
Publisher : SAS Institute
Page : 552 pages
File Size : 41,7 Mb
Release : 2010-02-15
Category : Computers
ISBN : 9781629590318

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Common Statistical Methods for Clinical Research with SAS Examples, Third Edition by Glenn Walker,Jack Shostak Pdf

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 : Glenn A. Walker,Jack Shostak
Publisher : Unknown
Page : 128 pages
File Size : 53,7 Mb
Release : 2010
Category : Medicine
ISBN : OCLC:742516275

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Common Statistical Methods for Clinical Research with SAS Examples by Glenn A. Walker,Jack Shostak Pdf

Author : Glenn A. Walker
Publisher : Sas Inst
Page : 464 pages
File Size : 49,8 Mb
Release : 2002
Category : Computers
ISBN : 1590470400

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Common Statistical Methods for Clinical Research with SAS Examples by Glenn A. Walker Pdf

This updated edition provides clinical researchers with an invaluable aid for understanding the statistical methods cited most frequently in clinical protocols, statistical analysis plans, clinical and statistical reports, and medical journals. The text is written in a way that takes the non-statistician through each test using examples, yet substantive details are presented that benefit even the most experienced data analysts.

Author : Alex Dmitrienko,Gary G. Koch
Publisher : SAS Institute
Page : 455 pages
File Size : 40,7 Mb
Release : 2017-07-17
Category : Computers
ISBN : 9781635261448

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Analysis of Clinical Trials Using SAS by Alex Dmitrienko,Gary G. Koch Pdf

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 : Ding-Geng (Din) Chen,Karl E. Peace,Pinggao Zhang
Publisher : CRC Press
Page : 378 pages
File Size : 49,6 Mb
Release : 2017-06-01
Category : Mathematics
ISBN : 9781498779531

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Clinical Trial Data Analysis Using R and SAS by Ding-Geng (Din) Chen,Karl E. Peace,Pinggao Zhang Pdf

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 : Thomas D. Cook,David L DeMets
Publisher : CRC Press
Page : 465 pages
File Size : 43,5 Mb
Release : 2007-11-19
Category : Mathematics
ISBN : 9781584880271

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Introduction to Statistical Methods for Clinical Trials by Thomas D. Cook,David L DeMets Pdf

Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.

Author : Kriss Harris,Richann Watson
Publisher : SAS Institute
Page : 198 pages
File Size : 51,7 Mb
Release : 2020-11-25
Category : Computers
ISBN : 9781952365973

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SAS Graphics for Clinical Trials by Example by Kriss Harris,Richann Watson Pdf

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.

Author : Mark Chang,John Balser,Jim Roach,Robin Bliss
Publisher : CRC Press
Page : 218 pages
File Size : 44,6 Mb
Release : 2019-03-20
Category : Mathematics
ISBN : 9781351214520

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Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials by Mark Chang,John Balser,Jim Roach,Robin Bliss Pdf

"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

Author : Chris Holland,Jack Shostak
Publisher : SAS Institute
Page : 294 pages
File Size : 52,5 Mb
Release : 2019-05-30
Category : Computers
ISBN : 9781642952414

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Implementing CDISC Using SAS by Chris Holland,Jack Shostak Pdf

For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to the Clinical Data Interchange Standards Consortium (CDISC) standards. Implementing CDISC Using SAS: An End-to-End Guide, Revised Second Edition, is an all-inclusive guide on how to implement and analyze the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submission. Updated to reflect the 2017 FDA mandate for adherence to CDISC standards, this new edition covers creating and using metadata, developing conversion specifications, implementing and validating SDTM and ADaM data, determining solutions for legacy data conversions, and preparing data for regulatory submission. The book covers products such as Base SAS, SAS Clinical Data Integration, and the SAS Clinical Standards Toolkit, as well as JMP Clinical. Topics included in this edition include an implementation of the Define-XML 2.0 standard, new SDTM domains, validation with Pinnacle 21 software, event narratives in JMP Clinical, STDM and ADAM metadata spreadsheets, and of course new versions of SAS and JMP software. The second edition was revised to add the latest C-Codes from the most recent release as well as update the make_define macro that accompanies this book in order to add the capability to handle C-Codes. The metadata spreadsheets were updated accordingly. Any manager or user of clinical trial data in this day and age is likely to benefit from knowing how to either put data into a CDISC standard or analyzing and finding data once it is in a CDISC format. If you are one such person--a data manager, clinical and/or statistical programmer, biostatistician, or even a clinician--then this book is for you.

Author : Alex Dmitrienko, Ph.D.,Christy Chuang-Stein, Ph.D.,Ralph B. D'Agostino,Sr., Ph.D.
Publisher : SAS Institute
Page : 464 pages
File Size : 45,5 Mb
Release : 2007-02-07
Category : Computers
ISBN : 9781629590301

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Pharmaceutical Statistics Using SAS by Alex Dmitrienko, Ph.D.,Christy Chuang-Stein, Ph.D.,Ralph B. D'Agostino,Sr., Ph.D. Pdf

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 : Geoff Der,Brian S. Everitt
Publisher : CRC Press
Page : 539 pages
File Size : 40,7 Mb
Release : 2012-10-01
Category : Mathematics
ISBN : 9781439867983

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Applied Medical Statistics Using SAS by Geoff Der,Brian S. Everitt Pdf

Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudi

Author : Thomas D. Cook,David L. DeMets
Publisher : CRC Press
Page : 452 pages
File Size : 42,8 Mb
Release : 2007-11-19
Category : Mathematics
ISBN : 9781420009965

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Introduction to Statistical Methods for Clinical Trials by Thomas D. Cook,David L. DeMets Pdf

Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors' collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various stati

Author : Geoff Der,Brian S. Everitt
Publisher : CRC Press
Page : 562 pages
File Size : 53,8 Mb
Release : 2012-10-01
Category : Mathematics
ISBN : 9781439867976

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Applied Medical Statistics Using SAS by Geoff Der,Brian S. Everitt Pdf

Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudinal and survival data analysis, missing data, generalized additive models (GAMs), and Bayesian methods. The book focuses on performing these analyses using SAS, the software package of choice for those analysing medical data. Features Covers the planning stage of medical studies in detail; several chapters contain details of sample size estimation Illustrates methods of randomisation that might be employed for clinical trials Covers topics that have become of great importance in the 21st century, including Bayesian methods and multiple imputation Its breadth and depth, coupled with the inclusion of all the SAS code, make this book ideal for practitioners as well as for a graduate class in biostatistics or public health. Complete data sets, all the SAS code, and complete outputs can be found on an associated website: http://support.sas.com/amsus

Author : Carol I. Matthews,Brian C. Shilling
Publisher : SAS Institute
Page : 229 pages
File Size : 54,8 Mb
Release : 2008
Category : Computers
ISBN : 9781599941288

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Validating Clinical Trial Data Reporting with SAS by Carol I. Matthews,Brian C. Shilling Pdf

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.