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SAS Programming in the Pharmaceutical Industry Second Edition

SAS Programming in the Pharmaceutical Industry  Second Edition Author Jack Shostak
ISBN-10 9781629591490
Release 2014-03-01
Pages 308
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This comprehensive resource provides on-the-job training for statistical programmers who use SAS in the pharmaceutical industry This one-stop resource offers a complete review of what entry- to intermediate-level statistical programmers need to know in order to help with the analysis and reporting of clinical trial data in the pharmaceutical industry. SAS Programming in the Pharmaceutical Industry, Second Edition begins with an introduction to the pharmaceutical industry and the work environment of a statistical programmer. Then it gives a chronological explanation of what you need to know to do the job. It includes information on importing and massaging data into analysis data sets, producing clinical trial output, and exporting data. This edition has been updated for SAS 9.4, and it features new graphics as well as all new examples using CDISC SDTM or ADaM model data structures. Whether you're a novice seeking an introduction to SAS programming in the pharmaceutical industry or a junior-level programmer exploring new approaches to problem solving, this real-world reference guide offers a wealth of practical suggestions to help you sharpen your skills. This book is part of the SAS Press program.

SAS Programming in the Pharmaceutical Industry

SAS Programming in the Pharmaceutical Industry Author Jack Shostak
ISBN-10 1590477936
Release 2005
Pages 332
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This real-world reference for clinical trial SAS programming is packed with solutions that can be applied day-to-day problems. Organized to reflect the statistical programmers workflow, this user-friendly text begins with an introduction to the working environment, then presents chapters on importing and massaging data into analysis data sets, producing clinical trial output, and exporting data.

Implementing CDISC Using SAS

Implementing CDISC Using SAS Author Chris Holland
ISBN-10 9781629605364
Release 2016-11-28
Pages 294
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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, 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 new edition include an implementation of the Define-XML 2.0 standard, new SDTM domains, validation with Pinnacle 21 software, event narratives in JMP Clinical, and of course new versions of SAS and JMP software. 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.

Validating Clinical Trial Data Reporting with SAS

Validating Clinical Trial Data Reporting with SAS Author Carol I. Matthews
ISBN-10 9781599941288
Release 2008
Pages 206
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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.

Pharmaceutical Statistics Using SAS

Pharmaceutical Statistics Using SAS Author Alex Dmitrienko
ISBN-10 9781599943572
Release 2007
Pages 464
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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.

Common Statistical Methods for Clinical Research with SAS Examples

Common Statistical Methods for Clinical Research with SAS Examples Author Glenn A. Walker
ISBN-10 9781607644255
Release 2010-02
Pages 552
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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.

Clinical Trials

Clinical Trials Author Duolao Wang
ISBN-10 9781901346725
Release 2006
Pages 480
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This book aims to demystify clinical trials. It is divided into five sections: fundamentals of trial design, alternative trial designs, basics of statistical analysis, special trial issues in data analysis, and reporting of trials. Using simple language the book explains with illustrations of numerous trial examples, the conceptual and methodological issues that occur at all stages of clinical trial covering trial design, conduct, analysis and reporting. The book is an educational and approachable reference in a difficult area of medicine where clinicians often feel uncertain and this material helps them review, appraise and publish trials and clinical evidence.

Analysis of Clinical Trials Using SAS

Analysis of Clinical Trials Using SAS Author Alex Dmitrienko
ISBN-10 1590477804
Release 2005-02-18
Pages 430
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In Analysis of Clinical Trials Using SAS: A Practical Guide, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge the gap between modern statistical methodology and real-world clinical trial applications. Step-by-step instructions illustrated with examples from actual trials and case studies serve to define a statistical method and its relevance in a clinical trials setting and to illustrate how to implement the method rapidly and efficiently using the power of SAS software. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials, including analysis of stratified data, incomplete data, multiple inferences, issues arising in safety and efficacy monitoring, and reference intervals for extreme safety and diagnostic measurements. Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience compiled in this book. Numerous ready-to-use SAS macros and example code are included. This book is part of the SAS Press program.

Handbook of Statistics in Clinical Oncology Third Edition

Handbook of Statistics in Clinical Oncology  Third Edition Author John Crowley
ISBN-10 9781439862001
Release 2012-03-26
Pages 657
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Many new challenges have arisen in the area of oncology clinical trials. New cancer therapies are often based on cytostatic or targeted agents, which pose new challenges in the design and analysis of all phases of trials. The literature on adaptive trial designs and early stopping has been exploding. Inclusion of high-dimensional data and imaging techniques have become common practice, and statistical methods on how to analyse such data have been refined in this area. A compilation of statistical topics relevant to these new advances in cancer research, this third edition of Handbook of Statistics in Clinical Oncology focuses on the design and analysis of oncology clinical trials and translational research. Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials, incorporating updates to all four parts: Phase I trials: Updated recommendations regarding the standard 3 + 3 and continual reassessment approaches, along with new chapters on phase 0 trials and phase I trial design for targeted agents. Phase II trials: Updates to current experience in single-arm and randomized phase II trial designs. New chapters include phase II designs with multiple strata and phase II/III designs. Phase III trials: Many new chapters include interim analyses and early stopping considerations, phase III trial designs for targeted agents and for testing the ability of markers, adaptive trial designs, cure rate survival models, statistical methods of imaging, as well as a thorough review of software for the design and analysis of clinical trials. Exploratory and high-dimensional data analyses: All chapters in this part have been thoroughly updated since the last edition. New chapters address methods for analyzing SNP data and for developing a score based on gene expression data. In addition, chapters on risk calculators and forensic bioinformatics have been added. Accessible to statisticians and oncologists interested in clinical trial methodology, the book is a single-source collection of up-to-date statistical approaches to research in clinical oncology.

Sample Size Calculations in Clinical Research

Sample Size Calculations in Clinical Research Author Shein-Chung Chow
ISBN-10 9780824748234
Release 2003-03-04
Pages 358
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Sample size calculation plays an important role in clinical research. It is not uncommon, however, to observe discrepancies among study objectives (or hypotheses), study design, statistical analysis (or test statistic), and sample size calculation. Focusing on sample size calculation for studies conducted during the various phases of clinical research and development, Sample Size Calculation in Clinical Research explores the causes of discrepancies and how to avoid them. This volume provides formulas and procedures for determination of sample size required not only for testing equality, but also for testing non-inferiority/superiority, and equivalence (similarity) based on both untransformed (raw) data and log-transformed data under a parallel-group design or a crossover design with equal or unequal ratio of treatment allocations. It contains a comprehensive and unified presentation of statistical procedures for sample size calculation that are commonly employed at various phases of clinical development. Each chapter includes, whenever possible, real examples of clinical studies from therapeutic areas such as cardiovascular, central nervous system, anti-infective, oncology, and women's health to demonstrate the clinical and statistical concepts, interpretations, and their relationships and interactions. The book highlights statistical procedures for sample size calculation and justification that are commonly employed in clinical research and development. It provides clear, illustrated explanations of how the derived formulas and/or statistical procedures can be used.

Carpenter s Guide to Innovative SAS Techniques

Carpenter s Guide to Innovative SAS Techniques Author Art Carpenter
ISBN-10 9781612902029
Release 2012-03-02
Pages 570
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Carpenter's Guide to Innovative SAS Techniques offers advanced SAS programmers an all-in-one programming reference that includes advanced topics not easily found outside the depths of SAS documentation or more advanced training classes. Art Carpenter has written fifteen chapters of advanced tips and techniques, including topics on data summary, data analysis, and data reporting. Special emphasis is placed on DATA step techniques that solve complex data problems. There are numerous examples that illustrate advanced techniques that take advantage of formats, interface with the macro language, and utilize the Output Delivery System. Additional topics include operating system interfaces, table lookup techniques, and the creation of customized reports.

Adaptive Design Theory and Implementation Using SAS and R Second Edition

Adaptive Design Theory and Implementation Using SAS and R  Second Edition Author Mark Chang
ISBN-10 9781482256598
Release 2014-12-01
Pages 706
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Get Up to Speed on Many Types of Adaptive Designs Since the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials. New to the Second Edition Twelve new chapters covering blinded and semi-blinded sample size reestimation design, pick-the-winners design, biomarker-informed adaptive design, Bayesian designs, adaptive multiregional trial design, SAS and R for group sequential design, and much more More analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switching New material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trials Twenty new SAS macros and R functions Enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials Covering even more adaptive designs, this book provides biostatisticians, clinical scientists, and regulatory reviewers with up-to-date details on this innovative area in pharmaceutical research and development. Practitioners will be able to improve the efficiency of their trial design, thereby reducing the time and cost of drug development.

Bioequivalence and Statistics in Clinical Pharmacology

Bioequivalence and Statistics in Clinical Pharmacology Author Scott D. Patterson
ISBN-10 1420034936
Release 2005-11-10
Pages 400
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Maintaining a practical perspective, Bioequivalence and Statistics in Clinical Pharmacology explores statistics used in day-to-day clinical pharmacology work. The book covers the methods needed to design, analyze, and interpret bioequivalence trials; explores when, how, and why these studies are performed as part of drug development; and demonstrates the proposed methods using real world examples. Drawing on knowledge gained directly from working in the pharmaceutical industry, the authors set the stage by describing the general role of statistics. Once the foundation of clinical pharmacology drug development, regulatory applications, and the design and analysis of bioequivalence trials are established, they move on to related topics in clinical pharmacology involving the use of cross-over designs. These include, but are not limited to, safety studies in Phase I, dose-response trials, drug interaction trials, food-effect and combination trials, QTc and other pharmacodynamic equivalence trials, and dose-proportionality trials. Purposefully designed to be instantly applicable, the book provides examples of SAS code so that the analysis described can be immediately implemented. The authors have made extensive use of the proc mixed procedures available in SAS. Each chapter includes a vignette based on co-author Scott Patterson's experience in the clinical pharmacology work place and all the data sets are taken from real trials. The authors delineate practical utility and objectives, provide real-world examples of the topic under discussion, and include statistical theory and applications. Technical theory, where extensive, is included in technical appendices at the end of the chapter. Each topic contains worked examples that illustrate the applications of the statistical techniques and their interpretation. The authors also develop statistical tools useful for other topics of clinical pharmacology - namely general safety testing, testing for proarrythmic potential, population pharmacokinetics, and dose-selection.

SAS Certification Prep Guide Base Programming for SAS 9 Third Edition

SAS Certification Prep Guide  Base Programming for SAS 9  Third Edition Author SAS Institute
ISBN-10 9781607645641
Release 2011-07-08
Pages 802
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New and experienced SAS users who want to prepare for the Base Programming for SAS 9 exam will find the SAS Certification Prep Guide: Base Programming for SAS 9 to be an invaluable, convenient, and comprehensive resource that covers all of the objectives tested on the exam. Major topics include importing and exporting raw data files, creating and modifying SAS data sets, and identifying and correcting data syntax and programming logic errors. You will also become familiar with the enhancements and new functionality that are available in SAS 9. Each chapter includes a quiz on the chapter's contents. This guide provides you with a solid study resource as well as a go-to reference for your library.

Analysis of Observational Health Care Data Using SAS

Analysis of Observational Health Care Data Using SAS Author Douglas E. Faries
ISBN-10 160764424X
Release 2014-11-07
Pages 452
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This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.

Risk Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS

Risk Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS Author Richard C. Zink
ISBN-10 9781629592329
Release 2014-07-01
Pages 268
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International guidelines recommend that clinical trial data should be actively reviewed or monitored; the well-being of trial participants and the validity and integrity of the final analysis results are at stake. Risk-based monitoring (RBM) makes use of central computerized review of clinical trial data and site metrics to determine if and when clinical sites should receive more extensive quality review or intervention. Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS describes analyses for RBM that incorporate and extend the recommendations of TransCelerate Biopharm Inc., methods to detect potential patient-or investigator misconduct, snapshot comparisons to more easily identify new or modified data, and other novel visual and analytical techniques to enhance safety and quality reviews. The analytical methods described enable the clinical trial team to take a proactive approach to data quality and safety to streamline clinical development activities and address shortcomings while the study is ongoing.

Learning SAS in the Computer Lab

Learning SAS in the Computer Lab Author Rebecca Elliott
ISBN-10 9780495559689
Release 2009-04-27
Pages 320
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LEARNING SAS IN THE COMPUTER LAB, 3RD EDITION, gets students up and running quickly with SAS. Explaining concepts and commands in clear steps, the authors provide SAS basics so students can successfully apply computing techniques to all types of statistics problems and acquire an appreciation of data analysis. This brief, affordable manual also ensures that students learn enough about programming with SAS to be able to find their way around the many SAS reference manuals that they will use in their professional activities. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.