Data Analysis Using Stata

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Author: Ulrich Kohler,Frauke Kreuter

Publisher: Stata Press

ISBN: 1597180076

Category: Computers

Page: 378

View: 874

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.

Data Analysis Using Stata, Third Edition

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Author: Ulrich Kohler,Frauke Kreuter

Publisher: Stata Press

ISBN: 9781597181105

Category: Mathematics

Page: 497

View: 4225

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks. The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand. Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

An Introduction to Survival Analysis Using Stata, Second Edition

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Author: Mario Cleves

Publisher: Stata Press

ISBN: 1597180416

Category: Computers

Page: 372

View: 4544

An Introduction to Survival Analysis Using Stata, Third Edition provides the foundation to understand various approaches for analyzing time-to-event data. It is not only a tutorial for learning survival analysis but also a valuable reference for using Stata to analyze survival data. Although the book assumes knowledge of statistical principles, simple probability, and basic Stata, it takes a practical, rather than mathematical, approach to the subject. This updated third edition highlights new features of Stata 11, including competing-risks analysis and the treatment of missing values via multiple imputation. Other additions include new diagnostic measures after Cox regression, Stata's new treatment of categorical variables and interactions, and a new syntax for obtaining prediction and diagnostics after Cox regression. After reading this book, you will understand the formulas and gain intuition about how various survival analysis estimators work and what information they exploit. You will also acquire deeper, more comprehensive knowledge of the syntax, features, and underpinnings of Stata's survival analysis routines.

Handbook of Statistical Analyses Using Stata, Fourth Edition

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Author: Brian S. Everitt,Sophia Rabe-Hesketh

Publisher: CRC Press

ISBN: 9781584887560

Category: Mathematics

Page: 352

View: 7395

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.

Multilevel and Longitudinal Modeling Using Stata

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Author: Sophia Rabe-Hesketh,Anders Skrondal

Publisher: Stata Press

ISBN: 1597180084

Category: Computers

Page: 317

View: 1674

Presenting a thorough and accessible treatment of generalized linear mixed models, also known as multilevel or hierarchical models, Multilevel and Longitudinal Modeling Using Stata explains the models and their assumptions, applies methods to real data using Stata, and shows how to interpret the results. Beginning with the comparatively simple random-intercept linear model without covariates, the text develops the mixed model from first principles, familiarizing the reader with terminology, summarizing and relating the widely used estimating strategies, and providing historical perspective. Once this mixed-model foundation has been established, the text smoothly transitions to random-intercept models with covariates and then to random-coefficient models. The middle chapters apply the concepts defined earlier for Gaussian models to models for binary responses (e.g., logit and probit), ordinal responses (e.g., ordered logit and ordered probit), and count responses (e.g., Poisson). Models with multiple levels of random variation are then considered, as well as models with crossed (nonnested) random effects. The most complete and up-to-date depiction of Stata’s capacity for fitting generalized linear mixed models, Multilevel and Longitudinal Modeling Using Stata serves as an ideal introduction for Stata users wishing to learn about this powerful data-analysis tool.

A Gentle Introduction to Stata, Second Edition

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Author: Alan C. Acock

Publisher: Stata Press

ISBN: 1597180432

Category: Computers

Page: 333

View: 3367

Updated to reflect the new features of Stata 11, A Gentle Introduction to Stata, Third Edition continues to help new Stata users become proficient in Stata. After reading this introductory text, you will be able to enter, build, and manage a data set as well as perform fundamental statistical analyses. New to the Third Edition A new chapter on the analysis of missing data and the use of multiple-imputation methods Extensive revision of the chapter on ANOVA Additional material on the application of power analysis The book covers data management; good work habits, including the use of basic do-files; basic exploratory statistics, including graphical displays; and analyses using the standard array of basic statistical tools, such as correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion. Rather than splitting these topics by their Stata implementation, the material on graphics and postestimation are woven into the text in a natural fashion. The author teaches Stata commands by using the menus and dialog boxes while still stressing the value of do-files. Each chapter includes exercises and real data sets are used throughout.

Data Analysis with Stata

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Author: Prasad Kothari

Publisher: Packt Publishing Ltd

ISBN: 1782173188

Category: Computers

Page: 176

View: 6692

Explore the big data field and learn how to perform data analytics and predictive modelling in STATA About This Book Visualize and analyse data in STATA to devise a business strategy Learn STATA programming and predictive modeling Discover how you can become a data scientist with the power of STATA Who This Book Is For This book is for all the professionals and students who want to learn STATA programming and apply predictive modelling concepts. This book is also very helpful for experienced STATA programmers as it provides advanced statistical modelling concepts and their application. What You Will Learn Perform important statistical tests to become a STATA data scientist Be guided through how to program in STATA Implement logistic and linear regression models Visualize and program the data in STATA Analyse survey data, time series data, and survival data Perform database management in STATA In Detail STATA is an integrated software package that provides you with everything you need for data analysis, data management, and graphics. STATA also provides you with a platform to efficiently perform simulation, regression analysis (linear and multiple) [and custom programming. This book covers data management, graphs visualization, and programming in STATA. Starting with an introduction to STATA and data analytics you'll move on to STATA programming and data management. Next, the book takes you through data visualization and all the important statistical tests in STATA. Linear and logistic regression in STATA is also covered. As you progress through the book, you will explore a few analyses, including the survey analysis, time series analysis, and survival analysis in STATA. You'll also discover different types of statistical modelling techniques and learn how to implement these techniques in STATA. Style and approach This book is a hands-onguide to STATA programming and statistical modelling providing many STATA code examples and taking. You through the working of the code in detail.

Regression Models for Categorical Dependent Variables Using Stata, Second Edition

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Author: J. Scott Long,Jeremy Freese

Publisher: Stata Press

ISBN: 1597180114

Category: Computers

Page: 527

View: 2760

After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample selection bias.

The Workflow of Data Analysis Using Stata

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Author: J. Scott Long

Publisher: Stata Press

ISBN: 9781597180474

Category: Mathematics

Page: 379

View: 1346

The Workflow of Data Analysis Using Stata, by J. Scott Long, is an essential productivity tool for data analysts. Long presents lessons gained from his experience and demonstrates how to design and implement efficient workflows for both one-person projects and team projects. After introducing workflows and explaining how a better workflow can make it easier to work with data, Long describes planning, organizing, and documenting your work. He then introduces how to write and debug Stata do-files and how to use local and global macros. After a discussion of conventions that greatly simplify data analysis the author covers cleaning, analyzing, and protecting data.

A Visual Guide to Stata Graphics, Second Edition

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Author: Michael N. Mitchell

Publisher: Stata Press

ISBN: 1597180394

Category: Computers

Page: 471

View: 2375

Whether you are new to Stata graphics or a seasoned veteran, A Visual Guide to Stata Graphics, Second Edition will teach you how to use Stata to make publication-quality graphs that will stand out and enhance your statistical results. With over 900 illustrated examples and quick-reference tabs, this book quickly guides you to the information you need for creating and customizing high-quality graphs for any types of statistical data.

An Introduction to Stata for Health Researchers

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Author: Svend Juul

Publisher: Stata Press

ISBN: 1597180106

Category: Computers

Page: 326

View: 8446

Designed to assist those working in health research, An Introduction to Stata for Health Researchers, explains how to maximize the versatile Strata program for data management, statistical analysis, and graphics for research. The first nine chapters are devoted to becoming familiar with Stata and the essentials of effective data management. The text is also a valuable companion reference for more advanced users. It covers a host of useful applications for health researchers including the analysis of stratified data via epitab and regression models; linear, logistic, and Poisson regression; survival analysis including Cox regression, standardized rates, and correlation/ROC analysis of measurements.

Data Management Using Stata

A Practical Handbook

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Author: Michael N. Mitchell

Publisher: Stata Press

ISBN: N.A

Category: Mathematics

Page: 387

View: 7617

Using simple language and illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis. Rather than focus on clusters of commands, the author takes a modular approach that enables readers to quickly identify and implement the necessary task without having to access background information first. Each section in the chapters presents a self-contained lesson that illustrates a particular data management task via examples, such as creating data variables and automating error checking. The text also discusses common pitfalls and how to avoid them and provides strategic data management advice. Ideal for both beginning statisticians and experienced users, this handy book helps readers solve problems and learn comprehensive data management skills.

A Stata® Companion to Political Analysis

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Author: Philip H. Pollock III

Publisher: CQ Press

ISBN: 1483370631

Category: Political Science

Page: 216

View: 1757

With Philip Pollock's Third Edition of A Stata Companion to Political Analysis, students quickly learn Stata via step-by-step instruction, more than 50 exercises, customized datasets, annotated screen shots, boxes that highlight Stata's special capabilities, and guidance on using Stata to read raw data. This attractive and value-priced workbook, an ideal complement to Pollock’s Essentials of Political Analysis, is a must-have for any political science student working with Stata.

Applied Statistics Using Stata

A Guide for the Social Sciences

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Author: Mehmet Mehmetoglu,Tor Georg Jakobsen

Publisher: SAGE

ISBN: 1473987903

Category: Social Science

Page: 376

View: 3317

Clear, intuitive and written with the social science student in mind, this book represents the ideal combination of statistical theory and practice. It focuses on questions that can be answered using statistics and addresses common themes and problems in a straightforward, easy-to-follow manner. The book carefully combines the conceptual aspects of statistics with detailed technical advice providing both the ‘why’ of statistics and the ‘how’. Built upon a variety of engaging examples from across the social sciences it provides a rich collection of statistical methods and models. Students are encouraged to see the impact of theory whilst simultaneously learning how to manipulate software to meet their needs. The book also provides: Original case studies and data sets Practical guidance on how to run and test models in Stata Downloadable Stata programmes created to work alongside chapters A wide range of detailed applications using Stata Step-by-step notes on writing the relevant code. This excellent text will give anyone doing statistical research in the social sciences the theoretical, technical and applied knowledge needed to succeed.

Flexible Parametric Survival Analysis Using Stata

Beyond the Cox Model

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Author: Patrick Royston,Paul C. Lambert

Publisher: Stata Press

ISBN: 9781597180795

Category: Mathematics

Page: 339

View: 6466

Through real-world case studies, this book shows how to use Stata to estimate a class of flexible parametric survival models. It discusses the modeling of time-dependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a particular disease when the cause of death has not been recorded. The book describes simple quantification of differences between any two covariate patterns through calculation of time-dependent hazard ratios, hazard differences, and survival differences.

An Introduction to Categorical Data Analysis

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Author: Alan Agresti

Publisher: Wiley

ISBN: 1119405262

Category: Mathematics

Page: 400

View: 4244

A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.

Epidemiology

Study Design and Data Analysis, Third Edition

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Author: Mark Woodward

Publisher: CRC Press

ISBN: 1482243202

Category: Mathematics

Page: 854

View: 5630

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems. New to the Third Edition New chapter on risk scores and clinical decision rules New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines Many more exercises and examples using both Stata and SAS More than 60 new figures After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding. Web Resource A wealth of supporting material can be downloaded from the book’s CRC Press web page, including: Real-life data sets used in the text SAS and Stata programs used for examples in the text SAS and Stata programs for special techniques covered Sample size spreadsheet

Using Stata for Quantitative Analysis

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Author: Kyle C. Longest

Publisher: SAGE Publications

ISBN: 1483356647

Category: Social Science

Page: 272

View: 5569

Using Stata for Quantitative Analysis, Second Edition offers a brief, but thorough introduction to analyzing data with Stata software. It can be used as a reference for any statistics or methods course across the social, behavioral, and health sciences since these fields share a relatively similar approach to quantitative analysis. In this book, author Kyle Longest teaches the language of Stata from an intuitive perspective, furthering students’ overall retention and allowing a student with no experience in statistical software to work with data in a very short amount of time. The self-teaching style of this book enables novice Stata users to complete a basic quantitative research project from start to finish. The Second Edition covers the use of Stata 13 and can be used on its own or as a supplement to a research methods or statistics textbook.

Regression Analysis for the Social Sciences

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Author: Rachel A. Gordon

Publisher: Routledge

ISBN: 1317607112

Category: Social Science

Page: 22

View: 7400

Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: •interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. •thorough integration of teaching statistical theory with teaching data processing and analysis. •teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.

Interpreting and Visualizing Regression Models Using Stata

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Author: Michael N. Mitchell

Publisher: Stata Press

ISBN: 9781597181075

Category: Mathematics

Page: 558

View: 6674

Michael Mitchell's Interpreting and Visualizing Regression Models Using Stata is a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is a boon to anyone who has to present the tangible meaning of a complex model in a clear fashion, regardless of the audience. As an example, many experienced researchers start to squirm when asked to give a simple explanation of the applied meaning of interactions in nonlinear models such as logistic regression. The tools in Mitchell's book make this task much more enjoyable and comprehensible. Mitchell starts with simple linear regression (which is simple in all ways), and then adds polynomials and discontinuities. This is followed by 2-way and 3-way interaction until interpretation of coefficients through words is difficult. By careful use of Stata's marginsplot command, Mitchell shows how well graphs can be used to show effects. He also includes careful verbal interpretation of coefficients to make communications complete. He then extends the methods from linear regression to various types of nonlinear regression, such as multilevel or survival models. A significant difference between this book and most others on regression models is that Mitchell spends quite some time on fitting and visualizing discontinuous models' models where the outcome can change value suddenly at thresholds. Such models are natural in settings such as education and policy evaluation, where graduation or policy changes can make sudden changes in income or revenue. This book is a worthwhile addition to the library of anyone involved in statistical consulting, teaching, or collaborative applied statistical environments.