Research Areas of Specialization: Methodology

The Department of Human Development and Family Studies at Penn State University has a long and distinguished record of doctoral training in developmental methods and the analysis of change. Faculty are working on both analytical and design innovations and on innovative applications to substantive research questions. Students can develop specializations in one or more areas, including latent variable modeling, time series modeling, non-stationary autoregressive moving average models, missing data analysis, hierarchical linear modeling, item response theory, mixture modeling, integrating variable and person-oriented analytic approaches in the analysis of change, experimental design, and methods for optimizing behavioral interventions. Our methodology faculty include:

  • Timothy Brick – Application of modern technology and computational methods in the study of processes of interaction and change across the lifespan.
  • Sy-Miin Chow – Longitudinal structural equation models; linear/nonlinear dynamic systems and state-space modeling techniques; mixture and regime-switching models; analysis of intensive longitudinal data.
  • Linda M. Collins – Quantitative methods for developing and optimizing behavioral interventions; experimental design; analysis of change in behavior and ability.
  • Eric Loken – Mixture models; item response theory; latent variable models; Bayesian inference; educational measurement; health and nutrition research.
  • Peter Molenaar – Dynamic systems analysis, analysis of neuro-cognitive (e.g., fMRI, EEG/MEG) data in collaboration with the Social, Life and Engineering Sciences Imaging Center (SLEIC) and the Penn State Milton S. Hershey Medical Center, person-specific and EMA data analysis.
  • Zita Oravecz – Study of individual differences from a process modeling perspective.
  • Nilam Ram – Analysis of longitudinal data; integration of variable and person-oriented approaches in the analysis of change; intraindividual study design.
  • Michael Rovine – Analysis of longitudinal data; structural equation modeling, multilevel modeling; nonstationary ARMA models; time series models, single subject models.

More information concerning the methodology faculty’s research interests and affiliated scientists/graduate students can be found at and One unique strength of our program is that methodology students are strongly encouraged to work with faculty in other areas of the Department of Human Development and Family Studies on topics related to individual development, prevention and intervention research, or family systems. Through these collaborations, students gain direct insights into substantive questions that motivate the development of advanced quantitative methods. Some examples of faculty who are closely affiliated with the methodology group include:

  • David Almeida – Daily diary methods; stress processes; multilevel modeling; assessment and modeling of biological markers; work and family linkages.
  • Bo Cleveland – Behavioral genetic methods, twin designs and association studies; experience sampling methods for studying substance use recovery.
  • Eva Lefkowitz – Observational methods, including within family interactions; content and affect coding of videotapes; self-report vs. observed data.
  • Jennifer Maggs – Adolescent social development and health; transition to adulthood; risk behaviors; prevention science; research methods.
  • Martin Sliwinski – Analysis of longitudinal, daily diary and experience sampling data; web-based survey and cognitive assessment; detection of early dementia.