Regression Models For Categorical Dependent Variables Using Stata Second Edition

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Regression Models For Categorical Dependent Variables Using Stata Third Edition

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Author : J. Scott Long
language : en
Publisher: Stata Press
Release Date : 2014-09-10

Regression Models For Categorical Dependent Variables Using Stata Third Edition written by J. Scott Long and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-10 with Mathematics categories.

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.

Regression Models For Categorical Dependent Variables Using Stata Second Edition

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Author : J. Scott Long
language : en
Publisher: Stata Press
Release Date : 2006

Regression Models For Categorical Dependent Variables Using Stata Second Edition written by J. Scott Long and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.

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.

Regression Models For Categorical Dependent Variables Using Stata

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Author : J. Scott Long
language : en
Publisher:
Release Date : 2006

Regression Models For Categorical Dependent Variables Using Stata written by J. Scott Long and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Regression analysis categories.

A Gentle Introduction To Stata Second Edition

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Author : Alan C. Acock
language : en
Publisher: Stata Press
Release Date : 2008-09-03

A Gentle Introduction To Stata Second Edition written by Alan C. Acock and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-03 with Computers categories.

"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.

Generalized Linear Models And Extensions Second Edition

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Author : James W. Hardin
language : en
Publisher: Stata Press
Release Date : 2007

Generalized Linear Models And Extensions Second Edition written by James W. Hardin and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

Deftly balancing theory and application, this book stands out in its coverage of the derivation of the GLM families and their foremost links. This edition has new sections on discrete response models, including zero-truncated, zero-inflated, censored, and hurdle count models, as well as heterogeneous negative binomial, and more.

Multilevel And Longitudinal Modeling Using Stata Second Edition

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Author : Sophia Rabe-Hesketh
language : en
Publisher: Stata Press
Release Date : 2008-02-07

Multilevel And Longitudinal Modeling Using Stata Second Edition written by Sophia Rabe-Hesketh and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-07 with Computers categories.

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.

Cite Right Second Edition

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Author : Charles Lipson
language : en
Publisher: University of Chicago Press
Release Date : 2011-05-15

Cite Right Second Edition written by Charles Lipson and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-15 with Language Arts & Disciplines categories.

In his bestselling guide, Doing Honest Work in College: How to Prepare Citations, Avoid Plagiarism, and Achieve Real Academic Success, veteran teacher Charles Lipson brought welcome clarity to the principles of academic honesty as well as to the often murky issues surrounding plagiarism in the digital age. Thousands of students have turned to Lipson for no-nonsense advice on how to cite sources properly—and avoid plagiarism—when writing their research papers. With his latest book, Cite Right, Lipson once again provides much-needed counsel in a concise and affordable handbook for students and researchers. Building on Doing Honest Work in College, Lipson’s new book offers a wealth of information on an even greater range of citation styles and details the intricacies of many additional kinds of sources. Lipson’s introductory essay, Why Cite, explains the reasons it is so important to use citations—and to present them accurately—in research writing. In subsequent chapters, Lipson explains the main citation styles students and researchers are likely to encounter in their academic work: Chicago; MLA; APA; CSE (biological sciences); AMA (medical sciences); ACS (chemistry, mathematics, and computer science); physics, astrophysics, and astronomy; Bluebook and ALWD (law); and AAA (anthropology and ethnography). His discussions of these styles are presented simply and clearly with examples drawn from a wide range of source types crossing all disciplines, from the arts and humanities to science, law, and medicine. Based on deep experience in the academic trenches, Cite Right is an accessible, one-stop resource—a must-have guide for students and researchers alike who need to prepare citations in any of the major disciplines and professional studies.

The Sage Handbook Of Regression Analysis And Causal Inference

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Author : Henning Best
language : en
Publisher: SAGE
Release Date : 2013-12-20

The Sage Handbook Of Regression Analysis And Causal Inference written by Henning Best and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-20 with Social Science categories.

′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.

Applied Regression Analysis

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Author : Christer Thrane
language : en
Publisher: Routledge
Release Date : 2019-10-16

Applied Regression Analysis written by Christer Thrane and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-16 with Business & Economics categories.

This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and perform it to perfection. This non-technical point of departure is complemented by practical examples of real-life data analysis using statistics software such as Stata, R and SPSS. Parts 1 and 2 of the book cover the basics, such as simple linear regression, multiple linear regression, how to interpret the output from statistics programs, significance testing and the key regression assumptions. Part 3 deals with how to practically handle violations of the classical linear regression assumptions, regression modeling for categorical y-variables and instrumental variable (IV) regression. Part 4 puts the various purposes of, or motivations for, regression into the wider context of writing a scholarly report and points to some extensions to related statistical techniques. This book is written primarily for those who need to do regression analysis in practice, and not only to understand how this method works in theory. The book’s accessible approach is recommended for students from across the social sciences.

Multivariate Analysis For The Biobehavioral And Social Sciences

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Author : Bruce L. Brown
language : en
Publisher: John Wiley & Sons
Release Date : 2011-11-01

Multivariate Analysis For The Biobehavioral And Social Sciences written by Bruce L. Brown and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-01 with Mathematics categories.

An insightful guide to understanding and visualizing multivariate statistics using SAS®, STATA®, and SPSS® Multivariate Analysis for the Biobehavioral and Social Sciences: A Graphical Approach outlines the essential multivariate methods for understanding data in the social and biobehavioral sciences. Using real-world data and the latest software applications, the book addresses the topic in a comprehensible and hands-on manner, making complex mathematical concepts accessible to readers. The authors promote the importance of clear, well-designed graphics in the scientific process, with visual representations accompanying the presented classical multivariate statistical methods . The book begins with a preparatory review of univariate statistical methods recast in matrix notation, followed by an accessible introduction to matrix algebra. Subsequent chapters explore fundamental multivariate methods and related key concepts, including: Factor analysis and related methods Multivariate graphics Canonical correlation Hotelling's T-squared Multivariate analysis of variance (MANOVA) Multiple regression and the general linear model (GLM) Each topic is introduced with a research-publication case study that demonstrates its real-world value. Next, the question "how do you do that?" is addressed with a complete, yet simplified, demonstration of the mathematics and concepts of the method. Finally, the authors show how the analysis of the data is performed using Stata®, SAS®, and SPSS®. The discussed approaches are also applicable to a wide variety of modern extensions of multivariate methods as well as modern univariate regression methods. Chapters conclude with conceptual questions about the meaning of each method; computational questions that test the reader's ability to carry out the procedures on simple datasets; and data analysis questions for the use of the discussed software packages. Multivariate Analysis for the Biobehavioral and Social Sciences is an excellent book for behavioral, health, and social science courses on multivariate statistics at the graduate level. The book also serves as a valuable reference for professionals and researchers in the social, behavioral, and health sciences who would like to learn more about multivariate analysis and its relevant applications.