Collegiate Affiliation

My research focuses on the development and application of advanced modeling and data mining approaches for the analysis of complex psychological data, and considers ways in which various substantive domains within psychology can be studied through these analytic approaches. To date, my research has addressed a number of key methodological problems and substantive questions. I have developed and utilized various data mining techniques to fit optimal structural equation and longitudinal growth models. In addition to data mining techniques, another aspect of my research interests is in estimation issues within SEM. Some of my current research utilizes integrative data analysis/data fusion methods to allow for the fitting of various longitudinal models that might not otherwise have been possible to fit to a single data set. I have also extended this data fusion approach to the Bayesian framework (Bayesian Synthesis).

I am also particularly interested in the application of advanced modeling techniques to the study of developmental and educational processes, with an emphasis on economically disadvantaged immigrant children. With funding from the National Institute of Health, over the next five years I will investigate ​​the complex associations among parenting, marginalization, and well-being during the COVID-19 pandemic. Understanding how parents fared during this time in a fully-powered, population-representative sample from across the life course is crucial to identifying mechanisms linking race, gender, and sexual identity marginalization to disparities in parental well-being with critical implications for child health.

Educational Background & Specialties
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Educational Background

  • PhD: Quantitative Psychology, Arizona State University
  • MA: Quantitative Psychology, University of California, Davis
  • BA: Psychology Major, Education Minor, University of California, Santa Barbara


  • Statistical learning and data mining
  • models for longitudinal data
  • big data analytics and modeling
  • Item response theory
  • Multilevel Modeling
  • Factor Analysis
  • Structural Equation Modeling
  • Longitudinal data analysis
  • Data fusion
  • Research Methodology and Statisitcal Analysis
  • R programming and data analysis
  • Integrative data analysis
  • growth and development