Applied Ordinal Logistic Regression Using Stata
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€105.99
A01=Xing Liu
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Author_Xing Liu
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Hierarchical linear models
Language_English
Logistic regression models
Multilevel modeling
Ordinal categorical data
Ordinal logistic regression
Ordinal regression models
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Quantitative methods
Single-level modeling
softlaunch
Stata
Statistical software
Product details
- ISBN 9781483319759
- Weight: 970g
- Dimensions: 187 x 231mm
- Publication Date: 16 Dec 2015
- Publisher: SAGE Publications Inc
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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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.
An open-access website for the book contains data sets, Stata code, and answers to in-text questions.
Xing Liu Ph.D., is a professor of educational research and assessment at Eastern Connecticut State University. He received his Ph.D. in measurement, evaluation, and assessment in the field of educational psychology from the University of Connecticut, Storrs. His interests include categorical data analysis, multilevel modeling, longitudinal data analysis, structural equation modeling, educational assessment, propensity score methods, data science, and Bayesian methods. He is the author of Applied Ordinal Logistic Regression Using Stata: From Single-Level to Multilevel Modeling (2016). His major publications focus on advanced statistical models. His articles have been recognized among the most popular papers published in the Journal of Modern Applied Statistical Methods (JMASM). Dr. Liu is the recipient of the Excellence Award in Creativity/Scholarship at Eastern Connecticut State University.
