Survival Analysis Using SAS

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Publisher : SAS Institute
ISBN 13 : 1599948842
Total Pages : 336 pages
Book Rating : 4.5/5 (999 download)

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Book Synopsis Survival Analysis Using SAS by : Paul D. Allison

Download or read book Survival Analysis Using SAS written by Paul D. Allison and published by SAS Institute. This book was released on 2010-03-29 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this fully updated new edition that incorporates the many enhancements in SAS procedures for survival analysis in SAS 9. Although the book assumes only a minimal knowledge of SAS, more experienced users will learn new techniques of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book, ensuring that even the uninitiated become sophisticated users of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered in survival analysis books, such as time-dependent covariates, competing risks, and repeated events. Survival Analysis Using SAS: A Practical Guide, Second Edition, has been thoroughly updated for SAS 9, and all figures are presented using ODS Graphics. This new edition also documents major enhancements to the STRATA statement in the LIFETEST procedure; includes a section on the PROBPLOT command, which offers graphical methods to evaluate the fit of each parametric regression model; introduces the new BAYES statement for both parametric and Cox models, which allows the user to do a Bayesian analysis using MCMC methods; demonstrates the use of the counting process syntax as an alternative method for handling time-dependent covariates; contains a section on cumulative incidence functions; and describes the use of the new GLIMMIX procedure to estimate random-effects models for discrete-time data. This book is part of the SAS Press program.

Survival Analysis Using SAS

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Publisher : SAS Press
ISBN 13 : 9781599946405
Total Pages : 324 pages
Book Rating : 4.9/5 (464 download)

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Book Synopsis Survival Analysis Using SAS by : Paul David Allison

Download or read book Survival Analysis Using SAS written by Paul David Allison and published by SAS Press. This book was released on 2010 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation of Survival Probabilities Confidence Intervals and Bands, mean life, median life Basic Plots Estimates of Hazards, log survival, etc. Basic plots Tests of equality of groups

Survival Analysis with Interval-Censored Data

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Author :
Publisher : CRC Press
ISBN 13 : 1351643053
Total Pages : 644 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Survival Analysis with Interval-Censored Data by : Kris Bogaerts

Download or read book Survival Analysis with Interval-Censored Data written by Kris Bogaerts and published by CRC Press. This book was released on 2017-11-20 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice. Features: -Provides an overview of frequentist as well as Bayesian methods. -Include a focus on practical aspects and applications. -Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website. The authors: Kris Bogaerts is project manager at I-BioStat, KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials. Arnošt Komárek is associate professor of statistics at Charles University, Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal. Emmanuel Lesaffre is professor of biostatistics at I-BioStat, KU Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification issues, and clinical trials. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics, and fellow of ISI and ASA.

Complex Survey Data Analysis with SAS

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Publisher : CRC Press
ISBN 13 : 1498776809
Total Pages : 341 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Complex Survey Data Analysis with SAS by : Taylor H. Lewis

Download or read book Complex Survey Data Analysis with SAS written by Taylor H. Lewis and published by CRC Press. This book was released on 2016-09-15 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.

Applied Survival Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 1118211588
Total Pages : 285 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Applied Survival Analysis by : David W. Hosmer, Jr.

Download or read book Applied Survival Analysis written by David W. Hosmer, Jr. and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.

Survival Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1475727283
Total Pages : 508 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Survival Analysis by : John P. Klein

Download or read book Survival Analysis written by John P. Klein and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.

Survival Analysis Using S

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Publisher : CRC Press
ISBN 13 : 0203501411
Total Pages : 277 pages
Book Rating : 4.2/5 (35 download)

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Book Synopsis Survival Analysis Using S by : Mara Tableman

Download or read book Survival Analysis Using S written by Mara Tableman and published by CRC Press. This book was released on 2003-07-28 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter written by Stephen Portnoy, censored regression quantiles - a new nonparametric regression methodology (2003) - is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the Kaplan-Meier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.

Biostatistics and Computer-based Analysis of Health Data Using SAS

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Author :
Publisher : Elsevier
ISBN 13 : 0081011717
Total Pages : 174 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Biostatistics and Computer-based Analysis of Health Data Using SAS by : Christophe Lalanne

Download or read book Biostatistics and Computer-based Analysis of Health Data Using SAS written by Christophe Lalanne and published by Elsevier. This book was released on 2017-06-22 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Survival Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1475725558
Total Pages : 332 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Survival Analysis by : David G. Kleinbaum

Download or read book Survival Analysis written by David G. Kleinbaum and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: A straightforward and easy-to-follow introduction to the main concepts and techniques of the subject. It is based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. A "user-friendly" layout includes numerous illustrations and exercises and the book is written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets. Each chapter concludes with practice exercises to help readers reinforce their understanding of the concepts covered, before going on to a more comprehensive test. Answers to both are included. Readers will enjoy David Kleinbaums style of presentation, making this an excellent introduction for all those coming to the subject for the first time.

Survival Analysis Using SAS

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Publisher :
ISBN 13 :
Total Pages : 292 pages
Book Rating : 4.:/5 (742 download)

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Book Synopsis Survival Analysis Using SAS by : Paul David Allison

Download or read book Survival Analysis Using SAS written by Paul David Allison and published by . This book was released on 2005 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Business Survival Analysis Using SAS

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Author :
Publisher : Independently Published
ISBN 13 :
Total Pages : 236 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis Business Survival Analysis Using SAS by : Jorge Ribeiro

Download or read book Business Survival Analysis Using SAS written by Jorge Ribeiro and published by Independently Published. This book was released on 2022-01-27 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve business problems involving time-to-event and resulting probabilities by following the modeling tutorials in Business Survival Analysis Using SAS: An Introduction to Lifetime Probabilities, the first book to be published in the field of business survival analysis! Survival analysis is a challenge. Books applying to health sciences exist, but nothing about survival applications for business has been available until now. Written for analysts, forecasters, econometricians, and modelers who work in marketing or credit risk and have little SAS modeling experience, Business Survival Analysis Using SAS builds on a foundation of SAS code that works in any survival model and features numerous annotated graphs, coefficients, and statistics linked to real business situations and data sets. This guide also helps recent graduates who know the statistics but do not necessarily know how to apply them get up and running in their jobs. By example, it teaches the techniques while avoiding advanced theoretical underpinnings so that busy professionals can rapidly deliver a survival model to meet common business needs. From first principles, this book teaches survival analysis by highlighting its relevance to business cases. A pragmatic introduction to survival analysis models, it leads you through business examples that contextualize and motivate the statistical methods and SAS coding. Specifically, it illustrates how to build a time-to-next-purchase survival model in SAS Enterprise Miner, and it relates each step to the underlying statistics and to Base SAS and SAS/STAT software. Following the many examples-from data preparation to validation to scoring new customers-you will learn to develop and apply survival analysis techniques to scenarios faced by companies in the financial services, insurance, telecommunication, and marketing industries, including the following scenarios: Time-to-next-purchase for marketing Employer turnover for human resources Small business portfolio macroeconometric stress tests for banks International Financial Reporting Standard (IFRS 9) lifetime probability of default for banks and building societies "Churn," or attrition, models for the telecommunications and insurance industries

Biostatistics Using JMP

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Publisher : SAS Institute
ISBN 13 : 1635262410
Total Pages : 356 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis Biostatistics Using JMP by : Trevor Bihl

Download or read book Biostatistics Using JMP written by Trevor Bihl and published by SAS Institute. This book was released on 2017-10-03 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyze your biostatistics data with JMP! Trevor Bihl's Biostatistics Using JMP: A Practical Guide provides a practical introduction on using JMP, the interactive statistical discovery software, to solve biostatistical problems. Providing extensive breadth, from summary statistics to neural networks, this essential volume offers a comprehensive, step-by-step guide to using JMP to handle your data. The first biostatistical book to focus on software, Biostatistics Using JMP discusses such topics as data visualization, data wrangling, data cleaning, histograms, box plots, Pareto plots, scatter plots, hypothesis tests, confidence intervals, analysis of variance, regression, curve fitting, clustering, classification, discriminant analysis, neural networks, decision trees, logistic regression, survival analysis, control charts, and metaanalysis. Written for university students, professors, those who perform biological/biomedical experiments, laboratory managers, and research scientists, Biostatistics Using JMP provides a practical approach to using JMP to solve your biostatistical problems.

A Handbook of Statistical Graphics Using SAS ODS

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Publisher : CRC Press
ISBN 13 : 1466599030
Total Pages : 250 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis A Handbook of Statistical Graphics Using SAS ODS by : Geoff Der

Download or read book A Handbook of Statistical Graphics Using SAS ODS written by Geoff Der and published by CRC Press. This book was released on 2014-08-15 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4. The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures. Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.

Survival Analysis Using the SAS® System

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Author :
Publisher :
ISBN 13 :
Total Pages : 292 pages
Book Rating : 4.:/5 (91 download)

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Book Synopsis Survival Analysis Using the SAS® System by : Paul David Allison

Download or read book Survival Analysis Using the SAS® System written by Paul David Allison and published by . This book was released on 2000 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Survival Analysis Using R

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Author :
Publisher : Springer
ISBN 13 : 3319312456
Total Pages : 226 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Applied Survival Analysis Using R by : Dirk F. Moore

Download or read book Applied Survival Analysis Using R written by Dirk F. Moore and published by Springer. This book was released on 2016-05-11 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.

Categorical Data Analysis Using SAS, Third Edition

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Author :
Publisher : SAS Institute
ISBN 13 : 1629590355
Total Pages : 590 pages
Book Rating : 4.6/5 (295 download)

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Book Synopsis Categorical Data Analysis Using SAS, Third Edition by : Maura E. Stokes

Download or read book Categorical Data Analysis Using SAS, Third Edition written by Maura E. Stokes and published by SAS Institute. This book was released on 2012-07-31 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians and researchers will find this book, newly updated for SAS/STAT 12.1, to be a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS.

Pharmaceutical Statistics Using SAS

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Publisher : SAS Institute
ISBN 13 : 1629590304
Total Pages : 464 pages
Book Rating : 4.6/5 (295 download)

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Book Synopsis Pharmaceutical Statistics Using SAS by : Alex Dmitrienko, Ph.D.

Download or read book Pharmaceutical Statistics Using SAS written by Alex Dmitrienko, Ph.D. and published by SAS Institute. This book was released on 2007-02-07 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.