Fulfilling this need, A Handbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9.

Author: Brian S. Everitt

Publisher: CRC Press

ISBN: 1584887567

Category: Mathematics

Page: 352

View: 937

With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, A Handbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many new features of Stata, including a new command for mixed models and a new matrix language. Each chapter describes the analysis appropriate for a particular application, focusing on the medical, social, and behavioral fields. The authors begin each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests, variance analysis, multiple linear regression, logistic regression, generalized linear models, survival analysis, random effects models, and cluster analysis. The core of the book centers on how to use Stata to perform analyses and how to interpret the results. The chapters conclude with several exercises based on data sets from different disciplines. A concise guide to the latest version of Stata, A Handbook of Statistical Analyses Using Stata, Fourth Edition illustrates the benefits of using Stata to perform various statistical analyses for both data analysis courses and self-study.

This handbook describes the features of Stata - an exciting statistical package used for standard and non-standard methods of data analysis.

Author: Sophia Rabe-Hesketh

Publisher: Chapman and Hall/CRC

ISBN: UOM:39015054008910

Category: Computers

Page: 215

View: 103

This handbook describes the features of Stata - an exciting statistical package used for standard and non-standard methods of data analysis. A Handbook of Statistical Analyses Using Stata shows outlines this package's usefulness in: modeling complex data from longitudinal studies or surveys analyzing results from clinical trials or epidemiological studies enabling tailor-made analyses with its powerful programming language Each chapter identifies the appropriate analysis for a particular set of data. A brief account of statistical background is included in each chapter, but the primary focus is on using Stata and interpreting results. This handbook complements its two predecessors A Handbook of Statistical Analyses Using S-Plus and A Handbook of Statistical Analyses Using SAS.

New users can get a head start and experienced users a quick reference in this edition which describes the features of version 8 of Stata in a concise, convenient format.

Author: Sophia Rabe-Hesketh

Publisher: Cambridge University Press

ISBN: 1584884045

Category: Computers

Page: 308

View: 955

New users can get a head start and experienced users a quick reference in this edition which describes the features of version 8 of Stata in a concise, convenient format. Each chapter also identifies the appropriate analysis for a particular set of data and includes a brief account of statistical background.

As such, this text complements the Stata manuals, offering both an ideal introduction to the program and a handy reference - perfect as a supplementary text for a second course in statistics.

Author: Brian S. Everitt

Publisher: Chapman and Hall/CRC

ISBN: 1584882018

Category: Mathematics

Page: 224

View: 602

Stata - the powerful statistical software package - has streamlined data analysis, interpretation, and presentation for researchers and statisticians around the world. Because of its power and extensive features, however, the Stata manuals are quite detailed and extensive. The Second Edition of A Handbook of Statistical Analyses using Stata describes the features of the latest version of Stata - Version 6 - in a concise, convenient format. It gives new users a head start on using the program and offers experienced users a quick reference. The authors illustrate how Stata can be used to apply a variety of statistical techniques, including regression, survival analysis, and principal components. They outline Stata's value in: modeling complex data from longitudinal studies or surveys analyzing results from clinical trials or epidemiological studies using its powerful programming language to apply tailor-made analyses relatively simply Each chapter deals with a particular data set, identifies the appropriate analysis for it, and includes a brief account of the statistical background of the technique applied. However, the primary focus is on using Stata 6 and interpreting results. As such, this text complements the Stata manuals, offering both an ideal introduction to the program and a handy reference - perfect as a supplementary text for a second course in statistics.

Ideal for researchers, statisticians, and students alike, this handbook forms a perfect complement to the Stata manuals, by giving new users a head start on using the program and providing experienced users with a handy quick reference.

Author: Sophia Rabe-Hesketh

Publisher: CRC Press

ISBN: 1439832358

Category: Mathematics

Page: 328

View: 605

The powerful statistical software Stata has streamlined data analysis, interpretation, and presentation for researchers and statisticians around the world. But because of its power and plethora of features, particularly in version 8, Stata manuals are usually quite extensive and detailed. The third edition of the Handbook of Statistical Analyses Using Stata describes the features of Stata version 8 in the same concise, convenient format that made the previous editions so popular. But the revisions updating the handbook to version 8 are not all this edition has to offer: the authors also added important material in three all-new chapters and focused more attention on Stata's improved graphical features. More Highlights of the Third Edition Ö Updates in all chapters that reflect the features of Stata 8 Ö A new chapter on random effects models Ö A new chapter on generalized estimating equations Ö A new chapter on cluster analysis Ö Increased emphasis on diagnostics Each chapter deals with a particular data set, identifies the appropriate analysis for it, and while it includes a brief account of the statistical background of the technique applied, the primary focus remains firmly on using Stata 8 and interpreting its results. Ideal for researchers, statisticians, and students alike, this handbook forms a perfect complement to the Stata manuals, by giving new users a head start on using the program and providing experienced users with a handy quick reference.

A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

Author: Torsten Hothorn

Publisher: Chapman and Hall/CRC

ISBN: 1584885394

Category: Mathematics

Page: 304

View: 741

R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

Intended for users of Stata who do not have a strong background in statistics or any experience of other statistical software packages.

Author: Alan C. Acock

Publisher: Stata Press

ISBN: 9781597180092

Category: Computers

Page: 289

View: 172

Providing the basic collection of statistical procedures used by social scientists, A Gentle Introduction to Stata presents the fundamental tools to learn Stata. The book begins with showing how to enter and manage data as well as perform basic descriptive statistics and graphical analysis. It then examines standard statistical procedures from a t test, nonparametric tests, measures of association, multiple regression, and logical regression. The book ends with guidelines for future work and advanced topics. This learning source is an excellent introduction for those with little statistical software experience while also a useful reference for more knowledgeable statisticians by offering a detailed index of commands.

Petitti, D. B. (2000), Meta-Analysis, Decision Analysis and Cost-Effectiveness Analysis, New York, USA: Oxford University ... A. (2008), Multilevel and
Longitudinal Modeling Using Stata, College Station, Texas, USA: Stata Press,
2nd edition.

Author: Torsten Hothorn

Publisher: CRC Press

ISBN: 9781482204582

Category: Mathematics

Page: 456

View: 119

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.

"This book provides a comprehensive introduction to Stata with an emphasis on data management, linear regression, logistic modeling, and using programs to automate repetitive tasks.

Author: Ulrich Kohler

Publisher: Stata Press

ISBN: 9781597180078

Category: Computers

Page: 378

View: 620

Provides an introduction to Stata with an emphasis on data management, linear regression, logistic modeling, and using programs to automate repetitive tasks. This book gives an introduction to the Stata interface and then proceeds with a discussion of Stata syntax and simple programming tools like for each loops.

An Introduction to Survival Analysis Using Stata , Stata Press , College Station ,
TX . Comstock , G.W. and ... Der , G. and Everitt , B.S. ( 2002 ) Handbook of Statistical Analysis using SAS Software , CRC Press , Boca Raton , FL . Everitt ,
B.S. ...

Author: Abdelmonem Afifi

Publisher: CRC Press

ISBN: 1584883081

Category: Mathematics

Page: 512

View: 229

Computer-Aided Multivariate Analysis, Fourth Edition enables researchers and students with limited mathematical backgrounds to understand the concepts underlying multivariate statistical analysis, perform analysis using statistical packages, and understand the output. New topics include Loess and Poisson regression, nominal and ordinal logistic regression, interpretation of interactions in logistic and survival analysis, and imputation for missing values. This book includes new exercises and references, and updated options in the latest versions of the statistical packages. All data sets and codebooks are available for download. The authors explain the assumptions made in performing each analysis and test, how to determine if your data meets those assumptions, and what to do if they do not. What to Watch out for sections in each chapter warn of common difficulties. By reading this text, you will know what method to use with your data set, how to get the results, and how to interpret them and explain them to others. New in the Fourth Edition: Expanded explanation of checking for goodness of fit in logistic regression and survival analysis Kaplan-Meier estimates of survival curves, formal tests for comparing survival between groups, interactions and the use of time-dependent covariates in survival analysis Expanded discussion of how to handle missing values Latest features of the S-PLUS package in addition to SAS, SPSS, STATA, and STATISTICA for multivariate analysis Data sets for the problems are available at the CRC web site: http://www.crcpress.com/product/isbn/9781584883081 Commands and output for examples used in the text for each statistical package are available at the UCLA web site: http://www.ats.ucla.edu/stat/examples/cama4/

Author: Lawrence C. HamiltonPublish On: 2012-08-28

... N. J. Cox editors Analyzing Health Equity Using Household Survey Data, O. O'
Donnell and others A Stata Companion to Political Analysis, P.H. Pollock III A Handbook of Statistical Analyses Using Stata, S. Rabe-Hesketh, B. Everitt
Multilevel ...

Author: Lawrence C. Hamilton

Publisher: Cengage Learning

ISBN: 9780840064639

Category: Mathematics

Page: 496

View: 632

For students and practicing researchers alike, STATISTICS WITH STATA Version 12 opens the door to the full use of the popular Stata program--a fast, flexible, and easy-to-use environment for data management and statistics analysis. Integrating Stata's impressive graphics, this comprehensive book presents hundreds of examples showing how to apply Stata to accomplish a wide variety of tasks. Like Stata itself, STATISTICS WITH STATA will make it easier for readers to move fluidly through the world of modern data analysis. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

This booklet reprints 33 'Stata Tips', from 2003-2006 of the Stata Journal. These articles described simple features of the software for enhancing and streamlining its usage.

Author: H. Joseph Newton

Publisher: Statacorp Lp

ISBN: 1597180181

Category: Computers

Page: 59

View: 686

This booklet reprints 33 'Stata Tips', from 2003-2006 of the Stata Journal. These articles described simple features of the software for enhancing and streamlining its usage.

Omar, R.Z. and Thompson, S.G. (2000) Analysis of a cluster randomized trial with
binary outcome data using a multi-level model. Statistics in Medicine, 19, ... Rabe
-Hesketh, S. and Everitt, B.S. (2007) A Handbook of Statistical Analyses Using Stata, 4th edn, Chapman & Hall/CRC Press, Boca Raton, FL. Richards, S.H. ...

Author: Michael J. Campbell

Publisher: John Wiley & Sons

ISBN: 9781118763605

Category: Medical

Page: 272

View: 195

A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials. The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. Written in a clear, accessible style Features real examples taken from the authors’ extensive practitioner experience of designing and analysing clinical trials Demonstrates the use of R, Stata and SPSS for statistical analysis Includes computer code so the reader can replicate all the analyses Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.

New to this edition are discussions of Longitudinal data analysis Randomized clinical trials Bayesian statistics GEE The bootstrap method Enhanced by a companion Web site providing data sets, selected problems and solutions, and examples ...

Author: Gerald van Belle

Publisher: John Wiley & Sons

ISBN: 9780471602354

Category: Medical

Page: 896

View: 142

A respected introduction to biostatistics, thoroughly updated andrevised The first edition of Biostatistics: A Methodology for the HealthSciences has served professionals and students alike as a leadingresource for learning how to apply statistical methods to thebiomedical sciences. This substantially revised Second Editionbrings the book into the twenty-first century for today’saspiring and practicing medical scientist. This versatile reference provides a wide-ranging look at basicand advanced biostatistical concepts and methods in a formatcalibrated to individual interests and levels of proficiency.Written with an eye toward the use of computer applications, thebook examines the design of medical studies, descriptivestatistics, and introductory ideas of probability theory andstatistical inference; explores more advanced statistical methods;and illustrates important current uses of biostatistics. New to this edition are discussions of Longitudinal data analysis Randomized clinical trials Bayesian statistics GEE The bootstrap method Enhanced by a companion Web site providing data sets, selectedproblems and solutions, and examples from such current topics asHIV/AIDS, this is a thoroughly current, comprehensive introductionto the field.

This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis.

Author: Michael N Mitchell

Publisher: Stata Press

ISBN: 1597183180

Category:

Page: 512

View: 138

This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats, the ability to write highly customized Excel files, the ability to have multiple Stata datasets open at once, and the ability to store and manipulate string variables stored as Unicode. Further, this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition, the chapters are organized by data management areas: reading and writing datasets, cleaning data, labeling datasets, creating variables, combining datasets, processing observations across subgroups, changing the shape of datasets, and programming for data management. Within each chapter, each section is a self-contained lesson illustrating a particular data management task (for instance, creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the "nuts and bolts" examples, author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management, while experienced users will find this information to be handy and time saving--there is a good chance that even the experienced user will learn some new tricks.

The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.

Author: David R. Boniface

Publisher: CRC Press

ISBN: 0412542307

Category: Mathematics

Page: 272

View: 912

Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research. The text covers: repeated measures unbalanced and non-randomized experiments and surveys choice of design adjustment for confounding variables model building and partition of variance covariance multiple regression Experiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.

Wright DB, London K. Modern Regression Techniques Using R: a Practical
Guide for Students and Researchers. Thousand Oaks, CA: Sage; ... A Handbook of Statistical Analyses Using SAS. 3rd ed. Boca Raton ... R for Stata Users. New
York: ...

Author: Stephen McKenzie

Publisher: Elsevier Health Sciences

ISBN: 9780729581493

Category: Medical

Page: 244

View: 210

Vital Statistics: an introduction to health science statistics e-book is a new Australian publication. This textbook draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student. It demonstrates how an understanding of statistics is useful in the real world, as well as in statistics exams. Vital Statistics: an introduction to health science statistics e-book is a relatively easy-to-read book that will painlessly introduce or re-introduce you to the statistical basics before guiding you through more demanding statistical challenges. Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics. It explores: How data relates to information, and how information relates to knowledge How to use statistics to distinguish information from disinformation The importance of probability, in statistics and in life That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be How to appropriately apply and interpret statistical measures of difference and association How qualitative and quantitative methods differ, and when it’s appropriate to use each The special statistical needs of the health sciences, and some especially health science relevant statistics The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses Real-life local examples of health statistics are presented, e.g. A study conducted at the Department of Obstetrics and Gynecology, University of Utah School of Medicine, explored whether there might be a systematic bias affecting the results of genetic specimen tests, which could affect their generalizability. Reader-friendly writing style t-tests/ ANOVA family of inferential statistics all use variants of the same basic formula Learning Objectives at the start of each chapter and Quick Reference Summaries at the end of each chapter provide the reader with a scope of the content within each chapter.

This textbook looks specifically at Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models.

Author: Sophia Rabe-Hesketh

Publisher: Stata Press

ISBN: 9781597180405

Category: Business & Economics

Page: 562

View: 945

This is a book about applied multilevel and longitudinal modeling. Other terms for multilevel models include hierarchical models, random-effects or random-coefficient models, mixed-effects models, or simply mixed models. Longitudinal data are also referred to as panel data, repeated measures, or cross-sectional time series. A popular type of multilevel model for longitudinal data is the growth-curve model. Our emphasis is on explaining the models and their assumptions, applying the methods to real data, and interpreting results.

Agresti A. Categorical Data Analysis. Wiley series in probability and statistics. 3rd
ed. Hoboken, NJ: John Wiley and Sons; 2012. Archer KJ, Lemeshow S.
Goodness-of-fit test for a logistic regression model fitted using survey sample
data. Stata ...

Author: Timothy P. Johnson

Publisher: John Wiley & Sons

ISBN: 9781118594742

Category: Medical

Page: 840

View: 544

A comprehensive guidebook to the current methodologies and practices used in health surveys A unique and self-contained resource, Handbook of Health Survey Methods presents techniques necessary for confronting challenges that are specific to health survey research. The handbook guides readers through the development of sample designs, data collection procedures, and analytic methods for studies aimed at gathering health information on general and targeted populations. The book is organized into five well-defined sections: Design and Sampling Issues, Measurement Issues, Field Issues, Health Surveys of Special Populations, and Data Management and Analysis. Maintaining an easy-to-follow format, each chapter begins with an introduction, followed by an overview of the main concepts, theories, and applications associated with each topic. Finally, each chapter provides connections to relevant online resources for additional study and reference. The Handbook of Health Survey Methods features: 29 methodological chapters written by highly qualified experts in academia, research, and industry A treatment of the best statistical practices and specific methodologies for collecting data from special populations such as sexual minorities, persons with disabilities, patients, and practitioners Discussions on issues specific to health research including developing physical health and mental health measures, collecting information on sensitive topics, sampling for clinical trials, collecting biospecimens, working with proxy respondents, and linking health data to administrative and other external data sources Numerous real-world examples from the latest research in the fields of public health, biomedicine, and health psychology Handbook of Health Survey Methods is an ideal reference for academics, researchers, and practitioners who apply survey methods and analyze data in the fields of biomedicine, public health, epidemiology, and biostatistics. The handbook is also a useful supplement for upper-undergraduate and graduate-level courses on survey methodology.