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Logistic Regression Models For Ordinal Response Variables
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Book Synopsis Logistic Regression Models for Ordinal Response Variables by : Ann A. O'Connell
Download or read book Logistic Regression Models for Ordinal Response Variables written by Ann A. O'Connell and published by SAGE. This book was released on 2006 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
Book Synopsis Analysis of Ordinal Categorical Data by : Alan Agresti
Download or read book Analysis of Ordinal Categorical Data written by Alan Agresti and published by John Wiley & Sons. This book was released on 2012-07-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data, Second Edition provides an introduction to basic descriptive and inferential methods for categorical data, giving thorough coverage of new developments and recent methods. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. Practitioners of statistics in government, industry (particularly pharmaceutical), and academia will want this new edition.
Book Synopsis Applied Ordinal Logistic Regression Using Stata by : Xing Liu
Download or read book Applied Ordinal Logistic Regression Using Stata written by Xing Liu and published by SAGE Publications. This book was released on 2015-09-30 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software. An open-access website for the book contains data sets, Stata code, and answers to in-text questions.
Book Synopsis Handbook of Regression Modeling in People Analytics by : Keith McNulty
Download or read book Handbook of Regression Modeling in People Analytics written by Keith McNulty and published by CRC Press. This book was released on 2021-07-29 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features: 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) Clear step-by-step instructions on executing the analyses Clear guidance on how to interpret results Primary instruction in R but added sections for Python coders Discussion exercises and data exercises for each of the main chapters Final chapter of practice material and datasets ideal for class homework or project work.
Book Synopsis Regression & Linear Modeling by : Jason W. Osborne
Download or read book Regression & Linear Modeling written by Jason W. Osborne and published by SAGE Publications. This book was released on 2016-03-24 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.
Book Synopsis Logistic Regression by : Scott W. Menard
Download or read book Logistic Regression written by Scott W. Menard and published by SAGE. This book was released on 2010 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.
Book Synopsis Logit and Probit by : Vani K. Borooah
Download or read book Logit and Probit written by Vani K. Borooah and published by SAGE. This book was released on 2002 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in the social sciences are amenable to analysis using the analytical tools of logit and probit models. This book explains what ordered and multinomial models are and also shows how to apply them to analysing issues in the social sciences.
Book Synopsis Ordered Regression Models by : Andrew S. Fullerton
Download or read book Ordered Regression Models written by Andrew S. Fullerton and published by CRC Press. This book was released on 2016-04-21 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives presents regression models for ordinal outcomes, which are variables that have ordered categories but unknown spacing between the categories. The book provides comprehensive coverage of the three major classes of ordered regression models (cumulative, stage, and adjacent) as well as variations based on the application of the parallel regression assumption. The authors first introduce the three "parallel" ordered regression models before covering unconstrained partial, constrained partial, and nonparallel models. They then review existing tests for the parallel regression assumption, propose new variations of several tests, and discuss important practical concerns related to tests of the parallel regression assumption. The book also describes extensions of ordered regression models, including heterogeneous choice models, multilevel ordered models, and the Bayesian approach to ordered regression models. Some chapters include brief examples using Stata and R. This book offers a conceptual framework for understanding ordered regression models based on the probability of interest and the application of the parallel regression assumption. It demonstrates the usefulness of numerous modeling alternatives, showing you how to select the most appropriate model given the type of ordinal outcome and restrictiveness of the parallel assumption for each variable. Web Resource More detailed examples are available on a supplementary website. The site also contains JAGS, R, and Stata codes to estimate the models along with syntax to reproduce the results.
Book Synopsis Fixed Effects Regression Models by : Paul D. Allison
Download or read book Fixed Effects Regression Models written by Paul D. Allison and published by SAGE Publications. This book was released on 2009-04-22 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models, logistic models, Poisson models, Cox regression models, and structural equation models. Both advantages and disadvantages of fixed-effects models will be considered, along with detailed comparisons with random-effects models. Written at a level appropriate for anyone who has taken a year of statistics, the book is appropriate as a supplement for graduate courses in regression or linear regression as well as an aid to researchers who have repeated measures or cross-sectional data.
Book Synopsis Regression Modeling Strategies by : Frank E. Harrell
Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".
Book Synopsis Regression Models for Categorical and Limited Dependent Variables by : J. Scott Long
Download or read book Regression Models for Categorical and Limited Dependent Variables written by J. Scott Long and published by SAGE. This book was released on 1997-01-09 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Best Practices in Logistic Regression by : Jason W. Osborne
Download or read book Best Practices in Logistic Regression written by Jason W. Osborne and published by SAGE Publications. This book was released on 2014-02-26 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.
Book Synopsis IBM SPSS Statistics 19 Statistical Procedures Companion by : Marija J. Norušis
Download or read book IBM SPSS Statistics 19 Statistical Procedures Companion written by Marija J. Norušis and published by Addison-Wesley Longman. This book was released on 2011-02-17 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: IBM SPSS Statistics 19 Statistical Procedures Companion contains tips, warnings, and examples that will help you take advantage of IBM SPSS Statistics 19 to better analyze data. This book contains a basic review of the underlying statistical concepts, with an emphasis on the practice of analyzing data. Ideal for both new and experienced users, this companion offers suggestions and strategies for handling the issues that arise when analyzing data. IBM SPSS Statistics 19 Statistical Procedures Companion covers various statistical procedures in IBM SPSS Statistics. This book also contains introductory chapters on using the software, creating and cleaning data files, testing hypotheses, and describing data.
Book Synopsis Handbook of Multilevel Analysis by : Jan Deleeuw
Download or read book Handbook of Multilevel Analysis written by Jan Deleeuw and published by Springer Science & Business Media. This book was released on 2007-12-26 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.
Book Synopsis Regression Models for Categorical Dependent Variables Using Stata, Second Edition by : J. Scott Long
Download or read book Regression Models for Categorical Dependent Variables Using Stata, Second Edition written by J. Scott Long and published by Stata Press. This book was released on 2006 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Interpreting Probability Models by : Tim Futing Liao
Download or read book Interpreting Probability Models written by Tim Futing Liao and published by SAGE. This book was released on 1994-06-30 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is the probability that something will occur, and how is that probability altered by a change in an independent variable? To answer these questions, Tim Futing Liao introduces a systematic way of interpreting commonly used probability models. Since much of what social scientists study is measured in noncontinuous ways and, therefore, cannot be analyzed using a classical regression model, it becomes necessary to model the likelihood that an event will occur. This book explores these models first by reviewing each probability model and then by presenting a systematic way for interpreting the results from each.
Book Synopsis The SAGE Handbook of Regression Analysis and Causal Inference by : Henning Best
Download or read book The SAGE Handbook of Regression Analysis and Causal Inference written by Henning Best and published by SAGE. This book was released on 2013-12-20 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′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.
