Applied Ordinal Logistic Regression Using Stata 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 Applied Ordinal Logistic Regression Using Stata PDF full book. Access full book title Applied Ordinal Logistic Regression Using Stata.
Author | : Xing Liu |
Publisher | : SAGE Publications |
Total Pages | : 372 |
Release | : 2015-09-30 |
Genre | : Social Science |
ISBN | : 1483319768 |
Download Applied Ordinal Logistic Regression Using Stata Book in PDF, ePub and Kindle
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.
Author | : Xing Liu |
Publisher | : |
Total Pages | : 528 |
Release | : 2016 |
Genre | : Regression analysis |
ISBN | : 9781071878972 |
Download Applied Ordinal Logistic Regression Using Stata Book in PDF, ePub and Kindle
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.
Author | : J. Scott Long |
Publisher | : Stata Press |
Total Pages | : 559 |
Release | : 2006 |
Genre | : Computers |
ISBN | : 1597180114 |
Download Regression Models for Categorical Dependent Variables Using Stata, Second Edition Book 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.
Author | : Jason W. Osborne |
Publisher | : SAGE Publications |
Total Pages | : 489 |
Release | : 2014-02-26 |
Genre | : Social Science |
ISBN | : 1483312097 |
Download Best Practices in Logistic Regression Book in PDF, ePub and Kindle
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.
Author | : Xing Liu |
Publisher | : SAGE Publications |
Total Pages | : 553 |
Release | : 2015-09-30 |
Genre | : Social Science |
ISBN | : 1483319741 |
Download Applied Ordinal Logistic Regression Using Stata Book in PDF, ePub and Kindle
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 by Xing Liu 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.
Author | : Ann A. O'Connell |
Publisher | : SAGE |
Total Pages | : 124 |
Release | : 2006 |
Genre | : Mathematics |
ISBN | : 9780761929895 |
Download Logistic Regression Models for Ordinal Response Variables Book in PDF, ePub and Kindle
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
Author | : Jason W. Osborne |
Publisher | : SAGE Publications |
Total Pages | : 489 |
Release | : 2016-03-24 |
Genre | : Psychology |
ISBN | : 1506302750 |
Download Regression & Linear Modeling Book in PDF, ePub and Kindle
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.
Author | : Andrew S. Fullerton |
Publisher | : CRC Press |
Total Pages | : 184 |
Release | : 2016-04-21 |
Genre | : Mathematics |
ISBN | : 1466569743 |
Download Ordered Regression Models Book in PDF, ePub and Kindle
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.
Author | : Scott W. Menard |
Publisher | : SAGE |
Total Pages | : 393 |
Release | : 2010 |
Genre | : Mathematics |
ISBN | : 1412974836 |
Download Logistic Regression Book in PDF, ePub and Kindle
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.
Author | : Alan Agresti |
Publisher | : John Wiley & Sons |
Total Pages | : 376 |
Release | : 2012-07-06 |
Genre | : Mathematics |
ISBN | : 1118209990 |
Download Analysis of Ordinal Categorical Data Book in PDF, ePub and Kindle
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.