Applied Ordinal Logistic Regressi Using Stata: From Single-Level to Multilevel Modeling by Xing Liu

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

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.