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Biostatistics and Computer-based Analysis of Health Data Using SAS

Biostatistics and Computer-based Analysis of Health Data Using SAS
  • Author : Christophe Lalanne,Mounir Mesbah
  • Publisher :Unknown
  • Release Date :2017-06-22
  • Total pages :174
  • ISBN : 9780081011713
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Summary : 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

Analysis in Nutrition Research

Analysis in Nutrition Research
  • Author : George Pounis
  • Publisher :Unknown
  • Release Date :2018-10-19
  • Total pages :408
  • ISBN : 9780128145579
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Summary : Analysis in Nutrition Research: Principles of Statistical Methodology and Interpretation of the Results describes, in a comprehensive manner, the methodologies of quantitative analysis of data originating specifically from nutrition studies. The book summarizes various study designs in nutrition research, research hypotheses, the proper management of dietary data, and analytical methodologies, with a specific focus on how to interpret the results of any given study. In addition, it provides a comprehensive overview of the methodologies used in study design and the management and analysis of collected data, paying particular attention to all of the available, modern methodologies and techniques. Users will find an overview of the recent challenges and debates in the field of nutrition research that will define major research hypotheses for research in the next ten years. Nutrition scientists, researchers and undergraduate and postgraduate students will benefit from this thorough publication on the topic. Provides a comprehensive presentation of the various study designs applied in nutrition research Contains a parallel description of statistical methodologies used for each study design Presents data management methodologies used specifically in nutrition research Describes methodologies using both a theoretical and applied approach Illustrates modern techniques in dietary pattern analysis Summarizes current topics in the field of nutrition research that will define major research hypotheses for research in the next ten years

Biostatistics and Computer-based Analysis of Health Data using R

Biostatistics and Computer-based Analysis of Health Data using R
  • Author : Christophe Lalanne,Mounir Mesbah
  • Publisher :Unknown
  • Release Date :2016-07-13
  • Total pages :206
  • ISBN : 9780081011751
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Summary : Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data. With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software. Features useful commands for describing a data table composed made up of quantitative and qualitative variables Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model

Applied Medical Statistics Using SAS

Applied Medical Statistics Using SAS
  • Author : Geoff Der,Brian S. Everitt
  • Publisher :Unknown
  • Release Date :2012-10-01
  • Total pages :559
  • ISBN : 9781439867983
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Summary : 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

Analyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users
  • Author : Monika Maya Wahi,Peter Seebach
  • Publisher :Unknown
  • Release Date :2017-11-22
  • Total pages :320
  • ISBN : 9781351394277
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Summary : Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful as a textbook for a descriptive or regression modeling class, as it uses a publicly-available dataset for examples, and provides exercises at the end of each chapter. For students and public health professionals, not only is it a gentle introduction to R, but it can serve as a guide to developing the results for a research report using R software. Features: Gives examples in both SAS and R Demonstrates descriptive statistics as well as linear and logistic regression Provides exercise questions and answers at the end of each chapter Uses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 data Guides the reader on producing a health analysis that could be published as a research report Gives an example of hypothesis-driven data analysis Provides examples of plots with a color insert

Analysis of Observational Health Care Data Using SAS

Analysis of Observational Health Care Data Using SAS
  • Author : Douglas E. Faries,Andrew C. Leon,Josep Maria Haro,Robert L. Obenchain
  • Publisher :Unknown
  • Release Date :2010-01-01
  • Total pages :436
  • ISBN : 1607642271
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Summary : 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.

Statistical Analysis of Medical Data Using SAS

Statistical Analysis of Medical Data Using SAS
  • Author : Geoff Der,Brian S. Everitt
  • Publisher :Unknown
  • Release Date :2005-09-20
  • Total pages :440
  • ISBN : 158488469X
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Summary : Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical literature. But while statistical software such as SAS make routine application of these techniques possible, users who are not primarily statisticians must take care to correctly implement the various procedures and correctly interpret the output. Statistical Analysis of Medical Data Using SAS demonstrates how to use SAS to analyze medical data. Each chapter addresses a particular analysis method. The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to "Displays," so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site or www.crcpress.com. Der and Everitt, authors of the best-selling Handbook of Statistical Analyses Using SAS, bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide--suitable for medical researchers and statisticians alike--to using SAS to analyze medical data.

Statistical Data Analysis Using SAS

Statistical Data Analysis Using SAS
  • Author : Mervyn G. Marasinghe,Kenneth J. Koehler
  • Publisher :Unknown
  • Release Date :2018-04-12
  • Total pages :679
  • ISBN : 9783319692395
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Summary : The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. New to this edition: • Covers SAS v9.2 and incorporates new commands • Uses SAS ODS (output delivery system) for reproduction of tables and graphics output • Presents new commands needed to produce ODS output • All chapters rewritten for clarity • New and updated examples throughout • All SAS outputs are new and updated, including graphics • More exercises and problems • Completely new chapter on analysis of nonlinear and generalized linear models • Completely new appendix Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.

Data Analysis Using SAS

Data Analysis Using SAS
  • Author : C.Y. Joanne Peng
  • Publisher :Unknown
  • Release Date :2008-08-28
  • Total pages :640
  • ISBN : 9781483342795
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Summary : Data Analysis Using SAS offers a comprehensive core text focused on key concepts and techniques in quantitative data analysis using the most current SAS commands and programming language. The coverage of the text is more evenly balanced among statistical analysis, SAS programming, and data/file management than any available text on the market. It provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems. Designed to be used in order of teaching preference by instructor, the book is comprised of two primary sections: the first half of the text instructs students in techniques for data and file managements such as concatenating and merging files, conditional or repetitive processing of variables, and observations. The second half of the text goes into great depth on the most common statistical techniques and concepts - descriptive statistics, correlation, analysis of variance, and regression - used to analyze data in the social, behavioral, and health sciences using SAS commands. A student study at www.sagepub.com/pengstudy comes replete with a multitude of computer programs, their output, specific details on how to check assumptions, as well as all data sets used in the book. Data Analysis Using SAS is a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.

Complex Survey Data Analysis with SAS

Complex Survey Data Analysis with SAS
  • Author : Taylor H. Lewis
  • Publisher :Unknown
  • Release Date :2016-09-15
  • Total pages :326
  • ISBN : 9781315349770
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Summary : 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.

Using SAS for Data Management, Statistical Analysis, and Graphics

Using SAS for Data Management, Statistical Analysis, and Graphics
  • Author : Ken Kleinman,Nicholas J. Horton
  • Publisher :Unknown
  • Release Date :2010-07-28
  • Total pages :305
  • ISBN : 1439827583
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Summary : Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics A unique companion for statistical coders, Using SAS for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in SAS, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods, and the creation of graphics. Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The text includes convenient indices organized by topic and SAS syntax. Demonstrating the SAS code in action and facilitating exploration, the authors present example analyses that employ a single data set from the HELP study. They also provide several case studies of more complex applications. Data sets and code are available for download on the book’s website. Helping to improve your analytical skills, this book lucidly summarizes the features of SAS most often used by statistical analysts. New users of SAS will find the simple approach easy to understand while more expert SAS programmers will appreciate the invaluable source of task-oriented information.

Applied Health Analytics and Informatics Using SAS

Applied Health Analytics and Informatics Using SAS
  • Author : Joseph M. Woodside
  • Publisher :Unknown
  • Release Date :2018-11-08
  • Total pages :378
  • ISBN : 9781635266146
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Summary : Leverage health data into insight! Applied Health Analytics and Informatics Using SAS describes health anamatics, a result of the intersection of data analytics and health informatics. Healthcare systems generate nearly a third of the world’s data, and analytics can help to eliminate medical errors, reduce readmissions, provide evidence-based care, demonstrate quality outcomes, and add cost-efficient care. This comprehensive textbook includes data analytics and health informatics concepts, along with applied experiential learning exercises and case studies using SAS Enterprise MinerTM within the healthcare industry setting. Topics covered include: Sampling and modeling health data – both structured and unstructured Exploring health data quality Developing health administration and health data assessment procedures Identifying future health trends Analyzing high-performance health data mining models Applied Health Analytics and Informatics Using SAS is intended for professionals, lifelong learners, senior-level undergraduates, graduate-level students in professional development courses, health informatics courses, health analytics courses, and specialized industry track courses. This textbook is accessible to a wide variety of backgrounds and specialty areas, including administrators, clinicians, and executives. This book is part of the SAS Press program.

Proceedings of the ... Public Health Conference on Records and Statistics

Proceedings of the ... Public Health Conference on Records and Statistics
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1985
  • Total pages :229
  • ISBN : STANFORD:36105223095477
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Summary :

Biostatistics and Computer-based Analysis of Health Data using Stata

Biostatistics and Computer-based Analysis of Health Data using Stata
  • Author : Christophe Lalanne,Mounir Mesbah
  • Publisher :Unknown
  • Release Date :2016-09-06
  • Total pages :134
  • ISBN : 9780081010846
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Summary : This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata 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 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 epideomological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential Stata packages and commands. Provides detailed examples of the use of Stata for common biostatistical tasks in medical research Features a work program structured around the four previous chapters and a series of practical exercises with commented corrections Includes an appendix to help the reader familiarize themselves with additional packages and commands Focuses on the practice of biostatistical methods that are essential to clinical research, epidemiology, and analysis of biomedical data

Proceedings of the 1985 Public Health Conference on Records and Statistics

Proceedings of the 1985 Public Health Conference on Records and Statistics
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1986
  • Total pages :525
  • ISBN : PURD:32754081678199
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Summary :

Biostatistics by Example Using SAS Studio

Biostatistics by Example Using SAS Studio
  • Author : Ron Cody
  • Publisher :Unknown
  • Release Date :2016-09-22
  • Total pages :262
  • ISBN : 9781629604930
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Summary : Learn how to solve basic statistical problems with Ron Cody's easy-to-follow style using the point-and-click SAS Studio tasks. Aimed specifically at the health sciences, Biostatistics by Example Using SAS Studio, provides an introduction to SAS Studio tasks. The book includes many biological and health-related problem sets and is fully compatible with SAS University Edition. After reading this book you will be able to understand temporary and permanent SAS data sets, and you will learn how to create them from various data sources. You will also be able to use SAS Studio statistics tasks to generate descriptive statistics for continuous and categorical data. The inferential statistics portion of the book covers the following topics: paired and unpaired t tests one-way analysis of variance N-way ANOVA correlation simple and multiple regression logistic regression categorical data analysis power and sample size calculations Besides describing each of these statistical tests, the book also discusses the assumptions that need to be met before running and interpreting these tests. For two-sample tests and N-way tests, nonparametric tests are also described. This book leads you step-by-step through each of the statistical tests with numerous screen shots, and you will see how to read and interpret all of the output generated by these tests. Experience with some basic statistical tests used to analyze medical data or classroom experience in biostatistics or statistics is required. Although the examples are related to the medical and biology fields, researchers in other fields such as psychology or education will find this book helpful. No programming experience is required. Loading data files into SAS University Edition? Click here for more information.

Statistics Catalog 2005

Statistics Catalog 2005
  • Author : Neil Thomson
  • Publisher :Unknown
  • Release Date :2004-09
  • Total pages :229
  • ISBN : 0534420451
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Summary :

SAS for Data Analysis

SAS for Data Analysis
  • Author : Mervyn G. Marasinghe,William J. Kennedy
  • Publisher :Unknown
  • Release Date :2008-12-10
  • Total pages :558
  • ISBN : 038777372X
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Summary : This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Introduction to Biostatistics with JMP

Introduction to Biostatistics with JMP
  • Author : Steve Figard
  • Publisher :Unknown
  • Release Date :2019-10-04
  • Total pages :288
  • ISBN : 9781635267181
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Summary : Explore biostatistics using JMP® in this refreshing introduction Presented in an easy-to-understand way, Introduction to Biostatistics with JMP® introduces undergraduate students in the biological sciences to the most commonly used (and misused) statistical methods that they will need to analyze their experimental data using JMP. It covers many of the basic topics in statistics using biological examples for exercises so that the student biologists can see the relevance to future work in the problems addressed. The book starts by teaching students how to become confident in executing the right analysis by thinking like a statistician then moves into the application of specific tests. Using the powerful capabilities of JMP, the book addresses problems requiring analysis by chi-square tests, t tests, ANOVA analysis, various regression models, DOE, and survival analysis. Topics of particular interest to the biological or health science field include odds ratios, relative risk, and survival analysis. The author uses an engaging, conversational tone to explain concepts and keep readers interested in learning more. The book aims to create bioscientists who can competently incorporate statistics into their investigative toolkits to solve biological research questions as they arise.

A Handbook of Statistical Graphics Using SAS ODS

A Handbook of Statistical Graphics Using SAS ODS
  • Author : Geoff Der,Brian S. Everitt
  • Publisher :Unknown
  • Release Date :2014-08-15
  • Total pages :244
  • ISBN : 9781466599031
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Summary : 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.

Medical Statistics And Computer Experiments (2nd Edition)

Medical Statistics And Computer Experiments (2nd Edition)
  • Author : Fang Ji-qian
  • Publisher :Unknown
  • Release Date :2014-07-24
  • Total pages :1016
  • ISBN : 9789814566797
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Summary : This volume consists of three parts: Part I comprises 11 chapters on the basic concepts of statistics, Part II consists of 10 chapters on multivariate statistics and Part III contains 12 chapters on design and analysis for medical research. The book is written using basic concepts and commonly used methods of design and analysis in medical statistics, incorporating the operation of statistical package SAS and 100 computer experiments for the important statistical phenomena related to each chapter. All necessary data, including reference answers for the exercises, SAS programs for all computer experiments and part of the examples, and data documents for 12 medical researches are available. The Chinese version of this book has been recommended as a textbook of statistics for postgraduate program by the Office of Education Research, Ministry of Education, People's Republic of China.