*Requirements assume Introduction to Regression and Linear Models and its Lab, and Advanced Regression and Nonlinear Models and its Lab as prerequisite courses

1. SSFD's Exploratory and Confirmatory Factor Analysis for the Social Sciences (introduction to matrix algebra, principal components analyses, exploratory factor analysis, confirmatory factor analysis, fundamentals of structural equation modeling)
2. SSFD's Structural Equation Modeling for the Social Sciences (theory and application of structural equation modeling; path analysis, latent regression models, multiple group analysis, models for longitudinal data)

*Students must complete 12 hours in elective courses. The below list is not exhaustive. The Quantitative Methodology Specialization elective hours can overlap with courses taken toward a degree program’s statistics electives requirements. Note that Introduction to Regression and Linear Models, Advanced Regression and Nonlinear Models, and Analysis of Variance courses do NOT count as electives for the Quantitative Methodology Specialization.

Advanced Modeling

• Pattern-Centered Analysis
• Bayesian Methods
• Advanced Bayesian Methods
• Experimental and Quasi-experimental Designs for Research

Measurement

• Item Response Theory
• Psychometrics

Statistical Methods for Small Group and Longitudinal Designs

• Analysis of Dyadic Interaction
• Structural Equation Modeling with Longitudinal Data
• Latent Growth and Mixture Models with Longitudinal Data

Statistical Methods for Large and Complex Samples

• Social Network Analysis
• Large/Secondary Dataset Analysis

*Appropriate substitutions will be considered by the Quantitative Methodology faculty if required courses are not offered within a reasonable timeframe (e.g., due to faculty sabbaticals or leaves of absence). Completion of the Quantitative Methodology Specialization requires that at least 12 hours of the requirements be taken within The Sanford School (not including the introduction sequence). All courses counting toward the Quantitative Methodology Specialization must be completed with a minimum grade of B-.

Faculty affiliated with the Quantitative Methodology Specialization and their methodological interests are as follows:

Natalie Eggum – latent variable modeling and longitudinal data analyses

Dawn DeLay – social network analysis, dyadic analysis, interdependent (nonindependent) data, and longitudinal social relationship models

Masumi Iida – multilevel modeling of intensive longitudinal methods, and dyadic data analysis

Justin Jager – structural equation modeling, latent growth modeling, pattern-centered analysis
(e.g., latent class analysis and growth-mixture modeling)

Roy Levy – psychometrics, item response theory, structural equation modeling, Bayesian networks, Bayesian inference, and assessment design

Connor Sheehan – Longitudinal methods, bio-statistics, demographic techniques, event history analysis.

Mengya Xia – Intensive longitudinal methods, structural equation modeling, mixture modeling (e.g., latent class analysis), multilevel modeling of longitudinal data, methods for modeling dynamic patterns (e.g., time-varying effect modeling)