Regression for Categorical Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression for Categorical Data write by Gerhard Tutz. This book was released on 2011-11-21. Regression for Categorical Data available in PDF, EPUB and Kindle. This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accompanied by an R package that contains data sets and code for all the examples.
Regression Models for Categorical, Count, and Related Variables
Regression Models for Categorical, Count, and Related Variables - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Models for Categorical, Count, and Related Variables write by John P. Hoffmann. This book was released on 2016-08-16. Regression Models for Categorical, Count, and Related Variables available in PDF, EPUB and Kindle. Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes—all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques. Appendices show how to estimate the models in SAS, SPSS, and R; provide a review of regression assumptions using simulations; and discuss missing data. A companion website includes downloadable versions of all the data sets used in the book.
Regression Models for Categorical and Limited Dependent Variables
Regression Models for Categorical and Limited Dependent Variables - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Models for Categorical and Limited Dependent Variables write by J. Scott Long. This book was released on 1997-01-09. Regression Models for Categorical and Limited Dependent Variables available in PDF, EPUB and Kindle. Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.
Regression Models for Categorical Dependent Variables Using Stata, Second Edition
Regression Models for Categorical Dependent Variables Using Stata, Second Edition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Models for Categorical Dependent Variables Using Stata, Second Edition write by J. Scott Long. This book was released on 2006. Regression Models for Categorical Dependent Variables Using Stata, Second Edition available in PDF, EPUB and Kindle. 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.
SPSS Statistics for Data Analysis and Visualization
SPSS Statistics for Data Analysis and Visualization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook SPSS Statistics for Data Analysis and Visualization write by Keith McCormick. This book was released on 2017-05-01. SPSS Statistics for Data Analysis and Visualization available in PDF, EPUB and Kindle. Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.
