Quantitative Methodology

The Sanford School (SSFD) offers specialized training for students interested in the study of Quantitative Methodology. The Quantitative Methodology specialization is open to any doctoral student in SSFD. Students choosing the Quantitative Methodology specialization will undertake in-depth study of statistical and measurement methodologies that offer great utility for research in human development, family studies, sociology, and education, among other areas. Faculty and students interested in quantitative methods study, evaluate, and develop statistical and measurement methods applicable to investigating issues in family and human development, sociology, and related fields. Students whose primary interest is in measurement, methods, and statistical modeling should complete the Quantitative Methodology specialization, along with additional coursework and research focused on quantitative methods. Students whose primary interest is in other substantive areas within Family and Human Development or Sociology but who would like to develop strength in measurement and statistical analysis should also consider the Quantitative Methodology specialization.

How to Apply:

The Quantitative Methodology specialization is open to any doctoral student in the Sanford School. Prospective students should apply either through the PhD in Family and Human Development program or the PhD in Sociology program. Please see the Graduate Handbook: Program in Family and Human Development or the Graduate Handbook: Program in Sociology for full descriptions of the application process. Existing students may apply for the Quantitative Methodology Specialization by completing PDF icon this form.

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

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

Masumi Iida – multilevel modeling of longitudinal and dyadic data

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

Holly O'Rourke - mediation analysis and statistical performance of mediation models, longitudinal mediation models, latent change score models, structural equation models for longitudinal data, statistical power

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

Monica Tsethlikai - structural equation modeling, Bayesian statistics for small samples, item response theory

Marilyn Thompson – structural equation modeling, factor analysis, measurement invariance, multilevel modeling of longitudinal and clustered data

Natalie Eggum – longitudinal data analyses within a structural equation model framework

Courses and Electives

Required Courses (6 hours)

*Requirements assume Quantitative Methods in the Social Sciences I, Lab I, Quantitative Methods in the Social Sciences II, and Lab II as prerequisites

  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)

Electives (12 hours)

*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 Quantitative Methods in the Social Sciences I and Quantitative Methods in the Social Sciences II courses do NOT count as an elective for the Quantitative Methodology specialization.

Advanced Modeling

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


  • Item Response Theory

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 Methodology faculty if required courses are not offered within a reasonable timeframe (e.g., due to faculty sabbaticals or other leaves of absence). Completion of the Quantitative Methodology specialization requires that at least 12 hours of the requirements be taken within the Sanford School (this does not include the introduction sequence). All courses counting toward the Quantitative Methodology specialization must be completed with a minimum grade of B-.

For additional information, please contact:

Natalie Eggum, Quantitative Methodology Specialization
Email: Natalie.Eggum@asu.edu