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Applied Ordinal Logistic Regression Using Stata
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Applied Ordinal Logistic Regression Using Stata
From Single-Level to Multilevel Modeling

  • Xing Liu - Eastern Connecticut State University
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December 2015 | 552 pages | SAGE Publications, Inc
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. 

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1. Stata Basics
Introduction to Stata  
Data Management  
Graphs  
A Summary of Stata Commands in this Chapter  
Exercises  
 
2. Review of Basic Statistics
Understand Your Data Using Descriptive Statistics  
Descriptive Statistics for Continuous Variables Using Stata  
Frequency Distribution for Categorical Variables Using Stata  
Independent Samples t-test Using Stata  
Paired Samples t-test  
Analysis of Variance (ANOVA)  
Correlation  
Simple Linear Regression  
Multiple Linear Regression  
Chi-Square Test  
Making Publication-Quality Tables Using Stata  
General Guidelines for Reporting Resutls  
A Summary of Stata Commands in this Chapter  
Exercises  
 
3. Logistic Regression for Binary Data
Logistic Regression Models: An Introduction  
Research Example and Description of the Data and Sample  
Logistic Regression with Stata: Commands and Output  
Summary of Stata Commands in this Chapter  
Exercises  
 
4. Proportional Odds Models for Ordinal Response Variables
Proportional Odds Models: An Introduction  
Research Example and Description of the Data and Sample  
Proportional Odds Models with Stata: Commands and Output  
Summary of Stata Commands in this Chapter  
Exercises  
 
5. Partial Proportional Odds Models and Generalized Ordinal Logistic Regression Models
Introduction  
Research Example and Description of the Data and Sample  
Partial Proportional Odds Models with Stata: Commands and Output  
Generalized Ordinal Logistic Regression Models with Stata: An Example  
Making Publication-Quality Tables  
Presenting the Results  
Summary of Stata Commands in this Chapter  
Exercises  
 
6. Continuation Ratio Models
Continuation Ratio Models: An Introduction  
Research Example and Description of the Data and Sample  
Continuation Ratio Models with Stata: Commands and Output  
Making Publication-Quality Tables  
Presenting the Results  
Summary of Stata Commands in this Chapter  
Exercises  
 
7. Adjacent Categories Logistic Regression Models
Adjacent Categories Models: An Introduction  
Research Example and Description of the Data and Sample  
Adjacent Categories Models with Stata: Commands and Output  
Presenting the Results  
Summary of Stata Commands in this Chapter  
 
8. Stereotype Logistic Regression Models
Stereotype Logistic Regression Models: An Introduction  
Research Example and Description of Data and Sample  
Stereotype Logistic Regression with Stata: Commands and Output  
Making Publication-Quality Tables  
Presenting the Results  
Summary of Stata Commands in this Chapter  
Exercises  
 
9. Ordinal Logistic Regression with Complex Survey Sampling Designs
Ordinal Logistic Regression with Complex Survey Sampling Designs: An Introduction  
Research Example and the Description of Data and Variables  
Data Analysis with Stata: Commands and Output  
Making Publication-Quality Tables  
Summary of Stata Commands in this Chapter  
Exercises  
 
10. Multilevel Modeling for Continuous and Binary Response Variables
Multilevel Modeling: An Introduction  
Multilevel Modeling for Continuous Outcome Variables  
Multilevel Modeling for Binary Outcome Variables  
Multilevel Modeling for Binary Outcome Variables with Stata: Commands and Output  
Making Publication-Quality Tables  
Reporting the Results  
 
11. Multilevel Modeling for Ordinal Response Variables
Multilevel Modeling for Ordinal Response Variables: An Introduction  
Research Example: Research Problem and Questions  
Building a Two-Level Model for Ordinal Response Variables with Stata: Commands and Output  
Making Publication-Quality Tables  
Presenting the Results  
Summary of Stata Commands in this Chapter  
Exercises  
 
12. Beyond Ordinal Logistic Regression Models: Ordinal Probit Regression Models and Multinomial Logistic Regression Models
Ordinal Probit Models  
Multinomial Logistic Regression Models  
Summary of Stata Commands in this Chapter  
Exercises  

Supplements

Instructor Resource Site
Datasets and Stata Code

Answers to In-Text Questions

In this book, Xing Liu offers a well-crafted book focused on the application of ordinal response models across fields. Readers will be equipped to competently handle a variety of statistical techniques from basic correlations to more advanced generalized ordered logistic regression models. This is an excellent resource for both new consumers of these statistical applications to seasoned veterans working on more complex issues related to ordinal response models. 

Jennifer Hayes Clark
University of Houston

Logistic regression can be difficult to understand. Without a book explaining the test in a plain and easy-to-understand matter, learners will feel lost and get frustrated. However, Applied Ordinal Logistic Regression Using Stata explains the concept clearly and provides practical codes and output.  Learners will find this book approachable and easy to follow. 

Lu Liu
University of La Verne

Sample Materials & Chapters

Chapter 1


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ISBN: 9781483319759
£54.00