Regression Models for Categorical Dependent Variables Using Stata, Second Edition PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Regression Models for Categorical Dependent Variables Using Stata, Second Edition PDF full book. Access full book title Regression Models for Categorical Dependent Variables Using Stata, Second Edition by J. Scott Long. Download full books in PDF and EPUB format.
Author: J. Scott Long
Publisher: Stata Press
ISBN: 1597180114
Category : Computers
Languages : en
Pages : 559
Get Book Here
Book Description
The goal of the book is to make easier to carry out the computations necessary for the full interpretation of regression nonlinear models for categorical outcomes usign Stata.
Author: J. Scott Long
Publisher: Stata Press
ISBN: 1597180114
Category : Computers
Languages : en
Pages : 559
Get Book Here
Book Description
The goal of the book is to make easier to carry out the computations necessary for the full interpretation of regression nonlinear models for categorical outcomes usign Stata.
Author: J. Scott Long
Publisher:
ISBN: 9786000039196
Category : Regression analysis
Languages : en
Pages : 527
Get Book Here
Book Description
Author: J. Scott Long
Publisher: Stata Press
ISBN: 9781597181112
Category : Mathematics
Languages : en
Pages : 589
Get Book Here
Book Description
Regression Models for Categorical Dependent Variables Using Stata, Third Edition shows how to use Stata to fit and interpret regression models for categorical data. The third edition is a complete rewrite of the book. Factor variables and the margins command changed how the effects of variables can be estimated and interpreted. In addition, the authors' views on interpretation have evolved. The changes to Stata and to the authors' views inspired the authors to completely rewrite their popular SPost commands to take advantage of the power of the margins command and the flexibility of factor-variable notation. The new edition will interest readers of a previous edition as well as new readers. Even though about 150 pages of appendixes were removed, the third edition is about 60 pages longer than the second. Although regression models for categorical dependent variables are common, few texts explain how to interpret such models; this text fills the void. With the book, Long and Freese provide a suite of commands for model interpretation, hypothesis testing, and model diagnostics. The new commands that accompany the third edition make it easy to include powers or interactions of covariates in regression models and work seamlessly with models estimated with complex survey data. The authors' new commands greatly simplify the use of margins, in the same way that the marginsplot command harnesses the power of margins for plotting predictions. The authors discuss how to use margins and their new mchange, mtable, and mgen commands to compute tables and to plot predictions. They also discuss how to use these commands to estimate marginal effects, averaged either over the sample or at fixed values of the regressors. The authors introduce and advocate a variety of new methods that use predictions to interpret the effect of variables in regression models. The third edition begins with an excellent introduction to Stata and follows with general treatments of the estimation, testing, fit, and interpretation of this class of models. New to the third edition is an entire chapter about how to interpret regression models using predictions—a chapter that is expanded upon in later chapters that focus on models for binary, ordinal, nominal, and count outcomes. Long and Freese use many concrete examples in their third edition. All the examples, datasets, and author-written commands are available on the authors' website, so readers can easily replicate the examples with Stata. This book is ideal for students or applied researchers who want to learn how to fit and interpret models for categorical data.
Author: MICHAEL N. MITCHELL
Publisher: Stata Press
ISBN: 9781597183215
Category :
Languages : en
Pages : 610
Get Book Here
Book Description
Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.
Author: Karen Robson
Publisher: SAGE
ISBN: 1473934303
Category : Social Science
Languages : en
Pages : 153
Get Book Here
Book Description
Have you been told you need to do multilevel modeling, but you can′t get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense? Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated. This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.
Author: Alan C. Acock
Publisher: Stata Press
ISBN: 1597180432
Category : Computers
Languages : en
Pages : 357
Get Book Here
Book Description
"A Gentle Introduction to Stata, Second Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text, new users will not only be able to use Stata well but also learn new aspects of Stata easily. Acock assumes that the user is not familiar with any statistical software. This assumption of a blank slate is central to the structure and contents of the book. Acock starts with the basics; for example, the portion of the book that deals with data management begins with a careful and detailed example of turning survey data on paper into a Stata-ready dataset on the computer. When explaining how to go about basic exploratory statistical procedures, Acock includes notes that should help the reader develop good work habits. This mixture of explaining good Stata habits and good statistical habits continues throughout the book. Acock is quite careful to teach the reader all aspects of using Stata. He 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 (correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion). Acock teaches Stata commands by using the menus and dialog boxes while still stressing the value of do-files. In this way, he ensures that all types of users can build good work habits. Each chapter has exercises that the motivated reader can use to reinforce the material. The tone of the book is friendly and conversational without ever being glib or condescending. Important asides and notes about terminology are set off in boxes, which makes the text easy to read without any convoluted twists or forward-referencing. Rather than splitting topics by their Stata implementation, Acock chose to arrange the topics as they would be in a basic statistics textbook; graphics and postestimation are woven into the material in a natural fashion. Real datasets, such as the General Social Surveys from 2002 and 2006, are used throughout the book. The focus of the book is especially helpful for those in psychology and the social sciences, because the presentation of basic statistical modeling is supplemented with discussions of effect sizes and standardized coefficients. Various selection criteria, such as semipartial correlations, are discussed for model selection. The second edition of the book has been updated to reflect new features in Stata 10 and includes a new chapter on the use of factor analysis to develop valid, reliable scale measures."--Publisher's website.
Author: Daniel Powers
Publisher: Emerald Group Publishing
ISBN: 1781906599
Category : Psychology
Languages : en
Pages : 330
Get Book Here
Book Description
This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
Author: J. Scott Long
Publisher: Stata Press
ISBN: 9781597180474
Category : Mathematics
Languages : en
Pages : 379
Get Book Here
Book Description
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.
Author: Sophia Rabe-Hesketh
Publisher: Stata Press
ISBN: 1597180408
Category : Computers
Languages : en
Pages : 598
Get Book Here
Book Description
This textbook looks specifically at Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are "mixed" because they allow fixed and random effects, and they are "generalized" because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables.
Author: Ulrich Kohler (Dr. phil.)
Publisher: Stata Press
ISBN: 1597180076
Category : Computers
Languages : en
Pages : 399
Get Book Here
Book Description
"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. Using data from a longitudinal study of private households in Germany, the book presents many examples from the social sciences to bring beginners up to speed on the use of Stata." -- BACK COVER.
