UGA Bulletin

Course Description

Quantitative analysis for family/social sciences research topics includes dependent variables that are categorical or otherwise inappropriate for typical regression methods, data that are interdependent (i.e., dyadic data), and classification techniques assessing unmeasured/latent group membership explaining heterogeneity among individuals. Students will also learn to perform statistical analyses.

Athena Title

Categorical and Dyadic Data

Prerequisite

HDFS 8830 or permission of department

Semester Course Offered

Offered every year.

Grading System

A - F (Traditional)

Student learning Outcomes

By the end of this course, students will develop the ability to understand and critically evaluate research using techniques covered in this class.
By the end of this course, students will develop the skills necessary to apply one or more of these techniques with your own data.
By the end of this course, students will develop the ability to interpret and present results using one or more of these techniques.
By the end of this course, students will develop the foundations upon which to learn more advanced techniques toward the three topics covered in this course.

Topical Outline

1. Course overview; Review of OLS regression
2. Topic 1: Categorical (manifest) dependent variables
• Logistic regression
• Generalized Linear model; Categorical variables in MLM and SEM
3. Topic 2: Dyadic data analysis
• Overview of Interdependent Data; Introduction to Dyadic Data Analysis
• Actor-Partner Interdependence Models (APIM)
• Longitudinal APIM
• Social Relations Models (SRM)
• SRM with roles
• One with Many; Intro to Social Network
4. Topic 3: Classification Techniques (i.e., Latent group membership)
• Cluster Analysis
• Finite Mixture Modeling: Latent Class Analysis
• Finite Mixture Modeling: Latent Profile Analysis

Syllabus

Public CV

publish

Categorical and Dyadic Data Analysis for Family and Social Sciences