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A Health Sciences Research Institute Core



Dr. Sidra Goldman-Mellor UC MercedDr. Sidra Goldman-Mellor - Director

Sidra Goldman-Mellor, Ph.D., is an Assistant Professor of Public Health whose research combines epidemiology and psychology methods to study mental health and suicidal behavior. She has published extensively on these topics using a variety of secondary data sources, including complex survey data, longitudinal cohort data, and hospital record data.

Sidra grew up in Tucson, Arizona. Sidra received her Ph.D. in Epidemiology from the University of California, Berkeley in 2012, and her B.A. in Anthropology from Cornell University in 2003.


Methodological Expertise:

  • Epidemiologic study design
  • Longitudinal models
  • Analysis of complex survey data
  • Propensity score matching
  • Multilevel Modeling
  • And more...
Current Research:
Sidra’s current research examines determinants of suicidal behavior, and health outcomes among individuals who have attempted suicide. Her work on this topic, which uses hospital data from California, is funded by the National Institutes of Health.

More about her substantive expertise and published work can be found here.

HSRI Biostats Staff - YueqiDr. Yueqi Yan  - Chief Biostatistician

Yueqi Yan, Ph.D., is the Chief Biostatistician of the Biostatistics and Data Support Center at UC Merced. His methodological expertise includes longitudinal design, finite mixture model, survival analysis, multilevel modeling, structural equation modeling, and generalized linear model. He has over 10 years of program evaluation experiences with federally funded research projects in the areas of children’s mental health prevention and intervention services, parenting programs, and family recovery services.

Yueqi grew up in China. He received his Ph.D. in social welfare and M.S.W. from University of Kansas.


Methodological Expertise:

  • Longitudinal analysis
  • Experimental / quasi-experimental design
  • Finite mixture model
  • Survival analysis
  • Multilevel modeling
  • Structural equation modeling
  • Generalized linear model
  • And more...


All our consultants hold Ph.D or M.S. degrees in statistics, biostatistics or allied fields. Graduate student consultants are supervised by senior statisticians or faculty.

Jessica Tounstine UC MercedDr. Jessica Trounstine

Jessica Trounstine, Ph.D., is Associate Professor of Political Science who studies local politics in the United States. Her work uses survey experiments, GIS mapping, instrumental variable analysis, survival analysis, ecological inference, and historical primary source analysis to study the process and quality of political representation in cities, suburbs, and rural America.

Jessica grew up in San Jose, California. She received her B.A. in political science from UC Berkeley in 1998 and her Ph.D. in political science from UC San Diego in 2004. Jessica worked as an assistant professor of political and public affairs at Princeton University from 2004-2009.

Current Research:

Jessica is currently finishing a book on the politics of segregation in America between 1890 and 2010 entitled Segregation by Design. Her published work can be found at

Methodological Experience:

  • Experiments
  • Instrumental variable models
  • Event history models
  • Spatial models
  • Case studies
  • Multilevel modeling
  • Regression discontinuity designs
  • And more…

Dr. Sandie Ha, Biostatistics UC MercedDr. Sandie Ha

Sandie Ha, Ph.D., is an Assistant Professor of Public Health at the University of California, Merced. Her research focuses on studying how various environmental exposures (e.g., air pollution, extreme temperature, pesticides) affect pregnancy and perinatal health outcomes including but not limited to gestational complications, stillbirth, preterm birth, and birth defects. She’s also interested in investigating how exposures during windows of developmental plasticity (e.g. pregnancy and early life) influences the risk of neurodevelopment in early childhood. Her other research interests include cardiovascular complications, asthma, cancer, and health disparity.

Sandie recieved her Ph.D. in Epidemiology and M.P.H. at the University of Florida, Gainesville. She received her B.S. in Biology/Physiology at the University of Washington, Seattle. 

Methodological expertise:

  • Epidemiologic study design
  • Observational studies
  • Repeated measures
  • Complex survey data
  • Big data
  • Spatial analyses / GIS data
  • Case-crossover analyses
  • Meta-analysis
  • Survival analysis
  • And more...

Dr. Irenee Beattie UC MercedDr. Irenee Beattie

Irenee Beattie, Ph.D., has focused her research on the sociology of education, social inequality (race, gender and class), adolescent transitions to adulthood, and law and social policy. A series of current projects examine variation in the effects of social capital on college outcomes by race, gender, and first generation college student status. Prior to attending graduate school, she was a Sixth grade teacher in East Palo Alto, CA through the Teach for America program, which solidified her longstanding interest in educational equality.

Irenee earned her B.A. in Social Psychology with a minor in Women’s Studies from Tufts University, and her M.A. and Ph.D. in Sociology from University of Arizona.

Methodological expertise:

  • Analysis of complex survey data
  • Longitudinal methods
  • General linear models
  • Event history (discrete-time) models
  • And more..

Dr_keke_Lai_Biostatistics_Center_UC_MercedDr. Keke Lai

Keke Lai, Ph.D., is an Assistant Professor of Quantitative Psychology. He conducts research in statistical methods for the behavioral, educational, and social sciences, and helps bridge the gap between methodology and substantive research. An overarching theme for his research is to improve the meaningfulness of scientific studies (i.e., how to do science in a more scientific manner).

Keke grew up in China. He received his Ph.D. in Quantitative Psychology from University of Notre Dame in 2012, and worked as a postdoctoral researcher at Arizona State University in 2012-2014.


Methodological Expertise:

  • Psychometrics especially structural equation modeling
  • Sample size planning and related issues (e.g., effect size, power, confidence interval, philosophy of science)
  • Longitudinal/multilevel data analysis
  • Bayesian statistics
  • Meta-analysis
  • Missing data analysis
  • And more...