Our lab aims to develop and apply statistical methods in the areas of developmental and health research.

• Peggy Wang
• Johnny Zhang
• Xin (Cynthia) Tong
• Qian (Jackie) Zhang
• Zhe (Jesse) Wang

If you are interested in joining the DHRM lab and an undergraduate student at Notre Dame, send the following to either ZhiyongZhang (at) nd.edu or LijuangWang (at) nd.edu:

• An email or cover letter indicating:
  1. why you are interested in the lab and
  2. when you would like to start
• List of courses you've taken and grades (unofficial transcript)

• Bayesian structural equation modeling (SEM)
  • Johnny Zhang
  • We are investigating a general Bayesian method for estimating SEM models through MCMC algorithm. The focus is on how to incorporate prior information efficiently into SEM models.
• Longitudinal study design
  • Peggy Wang & Johnny Zhang
  • We investigate how to plan the sample size for a longitudinal study - power analysis. We evaluate how the sample size, the number of measurement occasions, and missing data influence the power of a longitudinal study.
• Longitudinal mediation analysis
  • Peggy Wang, Johnny Zhang, & Ryne Estabrook
  • Mediation analysis is a methodological tool for testing the impact of variables on existing statistical effects. We propose a variation of the longitudinal mediation model by Cole and Maxwell (2003), tailored for the study of intervention research. We then apply several variations of our longitudinal intervention model to data from the ACTIVE study (Jobe et al., 2001) to test whether the impact of training on cognitively demanding everyday tasks is mediated by reasoning ability. The resulting model allows for testing of the training and mediation effects, as well as assumptions of stationarity that allow for more parsimonious model selection and inference on the long-term effect of the intervention.