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Validating Clinical Trial Data Reporting With Sas
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Book Synopsis Validating Clinical Trial Data Reporting with SAS by : Carol I. Matthews
Download or read book Validating Clinical Trial Data Reporting with SAS written by Carol I. Matthews and published by SAS Institute. This book was released on 2008 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Validating Clinical Trial Data Reporting with SAS (Hardcover Edition) by : Carol I. Matthews
Download or read book Validating Clinical Trial Data Reporting with SAS (Hardcover Edition) written by Carol I. Matthews and published by . This book was released on 2008-03-17 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Validation is a critical component to programming clinical trial analysis. Essential to effective validation is the programmer's understanding of the data with which they'll be working. If you don't understand how the data is arranged, the values that are reasonable for each variable, and the way the data should behave, you cannot ensure that the final result of your programming effort is complete or even appropriate. Therefore, to be a successful programmer in the pharmaceutical industry, you need to understand validation requirements and to learn how to make the code do the bulk of the work so that your programs are efficient as well as accurate. 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 (FDA). Authors Carol Matthews and Brian Shilling provide practical examples, explanations for why different techniques are helpful, and tips for avoiding errors in your output. Topics addressed include: Validation and pharmaceutical industry overviews Documentation and maintenance requirements discussions General techniques to facilitate validation Data importing and exporting Common data types Reporting and statistics Validating Clinical Trial Data Reporting with SAS is designed for SAS programmers who are new to the pharmaceutical industry as well as for those seeking a good foundation for validation in the SAS programming arena. Readers should have a working knowledge of Base SAS and a basic understanding of programming tasks in the pharmaceutical industry.
Book Synopsis Implementing CDISC Using SAS by : Chris Holland
Download or read book Implementing CDISC Using SAS written by Chris Holland and published by SAS Institute. This book was released on 2019-05-30 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Analysis of Clinical Trials Using SAS by : Alex Dmitrienko
Download or read book Analysis of Clinical Trials Using SAS written by Alex Dmitrienko and published by SAS Institute. This book was released on 2017-07-17 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Implementing CDISC Using SAS by : Chris Holland
Download or read book Implementing CDISC Using SAS written by Chris Holland and published by Sas Inst. This book was released on 2012-11-23 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have written 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 is an all-inclusive guide on how to implement and analyze Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submissions. Topics covered include 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. Anyone dealing with CDISC standards--including SAS or JMP programmers, statisticians, and data managers in the pharmaceutical, biotechnology, or medical device industries--will find the philosophical best practices and implementation examples in this book invaluable.SAS Products and Releases: Base SAS: 9.3 JMP: 9.0.2, 10.0.2, 10.0.1, 10.0 JMP Clinical: 4.0, 3.1, 3.0, 2.1 SAS Clinical Data Integration: 2.3 SAS Clinical Standards Toolkit: 1.4, 1.3, 1.2 Operating Systems: All
Book Synopsis Clinical Trial Data Analysis Using R and SAS by : Ding-Geng (Din) Chen
Download or read book Clinical Trial Data Analysis Using R and SAS written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2017-06-01 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Clinical Trials written by Duolao Wang and published by Remedica. This book was released on 2006 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains statistics specifically for a medically literate audience. Readers gain not only an understanding of the basics of medical statistics, but also a critical insight into how to review and evaluate clinical trial evidence.
Book Synopsis Implementing CDISC Using SAS by : Chris Holland
Download or read book Implementing CDISC Using SAS written by Chris Holland and published by . This book was released on 2020-07-24 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Clinical Data Quality Checks for CDISC Compliance Using SAS by : Sunil Gupta
Download or read book Clinical Data Quality Checks for CDISC Compliance Using SAS written by Sunil Gupta and published by CRC Press. This book was released on 2019-09-23 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical Data Quality Checks for CDISC Compliance using SAS is the first book focused on identifying and correcting data quality and CDISC compliance issues with real-world innovative SAS programming techniques such as Proc SQL, metadata and macro programming. Learn to master Proc SQL’s subqueries and summary functions for multi-tasking process. Drawing on his more than 25 years’ experience in the pharmaceutical industry, the author provides a unique approach that empowers SAS programmers to take control of data quality and CDISC compliance. This book helps you create a system of SDTM and ADaM checks that can be tracked for continuous improvement. How often have you encountered issues such as missing required variables, duplicate records, invalid derived variables and invalid sequence of two dates? With the SAS programming techniques introduced in this book, you can start to monitor these and more complex data and CDISC compliance issues. With increased standardization in SDTM and ADaM specifications and data values, codelist dictionaries can be created for better organization, planning and maintenance. This book includes a SAS program to create excel files containing unique values from all SDTM and ADaM variables as columns. In addition, another SAS program compares SDTM and ADaM codelist dictionaries with codelists from define.xml specifications. Having tools to automate this process greatly saves time from doing it manually. Features SDTMs and ADaMs Vitals SDTMs and ADaMs Data CDISC Specifications Compliance CDISC Data Compliance Protocol Compliance Codelist Dictionary Compliance
Book Synopsis SAS Programming in the Pharmaceutical Industry by : Jack Shostak
Download or read book SAS Programming in the Pharmaceutical Industry written by Jack Shostak and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis SAS Programming in the Pharmaceutical Industry, Second Edition by : Jack Shostak
Download or read book SAS Programming in the Pharmaceutical Industry, Second Edition written by Jack Shostak and published by SAS Institute. This book was released on 2014-03-01 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Clinical Trial Data Analysis Using R and SAS by : Ding-Geng Chen
Download or read book Clinical Trial Data Analysis Using R and SAS written by Ding-Geng Chen and published by CRC Press. This book was released on 2020-12-18 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Introduction to Creating Standardized Clinical Trial Data with SAS by : Todd Case
Download or read book An Introduction to Creating Standardized Clinical Trial Data with SAS written by Todd Case and published by SAS Institute. This book was released on 2022-08-17 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: An indispensable guide for statistical programmers in the pharmaceutical industry. Statistical programmers in the pharmaceutical industry need to create standardized clinical data using rules created and governed by the Clinical Data Interchange Standards Consortium (CDISC). This book introduces the basic concepts, pharmaceutical industry knowledge, and SAS programming practices that every programmer needs to know to comply with regulatory requirements. Step-by-step, you will learn how data should be structured at each stage of the process from annotating electronic Case Report Forms (eCRFs) and defining the relationship between SDTM and ADaM, to understanding how to generate a Define-XML file to transmit metadata. Filled with clear explanations and example code, this book focuses only on the essential information that entry-level programmers need to succeed.
Book Synopsis Cody's Data Cleaning Techniques Using SAS, Third Edition by : Ron Cody
Download or read book Cody's Data Cleaning Techniques Using SAS, Third Edition written by Ron Cody and published by SAS Institute. This book was released on 2017-03-15 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in Ron Cody's signature informal, tutorial style, this book develops and demonstrates data cleaning programs and macros that you can use as written or modify which will make your job of data cleaning easier, faster, and more efficient. --
Book Synopsis SAS for Epidemiologists by : Charles DiMaggio
Download or read book SAS for Epidemiologists written by Charles DiMaggio and published by Springer Science & Business Media. This book was released on 2012-10-25 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude of examples. It is directly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a “hands on” approach to the use of SAS for a broad number of epidemiologic analyses, readers learn techniques for data entry and cleaning, categorical analysis, ANOVA, and linear regression and much more. Exercises utilizing real-world data sets are featured throughout the book. SAS screen shots demonstrate the steps for successful programming. SAS (Statistical Analysis System) is an integrated system of software products provided by the SAS institute, which is headquartered in California. It provides programmers and statisticians the ability to engage in many sophisticated statistical analyses and data retrieval and mining exercises. SAS is widely used in the fields of epidemiology and public health research, predominately due to its ability to reliably analyze very large administrative data sets, as well as more commonly encountered clinical trial and observational research data.
Book Synopsis Modern Approaches to Clinical Trials Using SAS by : Sandeep Menon
Download or read book Modern Approaches to Clinical Trials Using SAS written by Sandeep Menon and published by SAS Institute. This book was released on 2015-12-09 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS by : Richard C. Zink
Download or read book Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS written by Richard C. Zink and published by SAS Institute. This book was released on 2014-07-01 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve efficiency while reducing costs in clinical trials with centralized monitoring techniques using JMP and SAS. 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. Traditional interpretation of this guidance for pharmaceutical trials has led to extensive on-site monitoring, including 100% source data verification. On-site review is time consuming, expensive (estimated at up to a third of the cost of a clinical trial), prone to error, and limited in its ability to provide insight for data trends across time, patients, and clinical sites. In contrast, 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 presents a practical implementation of methodologies within JMP Clinical for the centralized monitoring of clinical trials. Focused on intermediate users, this book 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. Further discussion highlights recent regulatory guidance documents on risk-based approaches, addresses the requirements for CDISC data, and describes methods to supplement analyses with data captured external to the study database. Given the interactive, dynamic, and graphical nature of JMP Clinical, any individual from the clinical trial team - including clinicians, statisticians, data managers, programmers, regulatory associates, and monitors - can make use of this book and the numerous examples contained within to streamline, accelerate, and enrich their reviews of clinical trial data. The analytical methods described in Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS 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. This book is part of the SAS Press
