Data & Methods

Data and Methods

Since its inception, OPR has been at the forefront of generating new sources of large-scale data to expand our understanding of human populations here and around the world, and developing cutting edge, innovative methods for statistical, demographic, qualitative and mixed methods analysis.

New data produced by current OPR associates include the Mexican Migration Project) and the Latin American Migration Project) to understand the processes drawing migrants primarily from the developing world to developed countries, particularly the United States (Massey), the The Future of Families and Child Wellbeing) that for more than two decades has been following a cohort of nearly 5,000 U.S.-born children from low-income and minority families that are at a high risk of breaking up and living in poverty, more than 5,500 hours of in-home video on parent-child interactions aimed at understanding how parents support their children’s early learning (Espenshade), and large-scale surveys in Guatemala on the determinants of illness and health care choices and in Taiwan on health among older persons (Goldman).

Current research in advancing the study of methods has included randomized controlled trials (Deaton), the development of theoretical models to investigate the population dynamics of infectious diseases (Grenfell; Metcalf), new quantitative statistical methods for applications across the social sciences and, in particular, tools that facilitate automated text analysis and model complex heterogeneity in regression (Stewart) and propensity score analysis (Yu Xie), and social network studies of hidden populations (Salganik).


Noreen Goldman

  • New Jersey Alliance for Clinical Translational Science: NJ ACTS
  • Social Disparities in Physical Functioning by Race, Ethnicity, and Immigration Status

Bryan Grenfell

  • Application of Epidemiological Models to Guide and Evaluate Control of Vaccine-preventable Infections
  • Exploring Predictive Models for Improving Influenza Vaccine Virus Selection
  • Modeling the Impact of Complex Drivers on Infectious Disease Dynamics and Control
  • Modeling the Risk of Measles Outbreaks and the Effectiveness of Public Health Response Strategies in the United States

C. Jessica E. Metcalf

  • Assessing the Feasibility of Using Serological Data to Monitor and Guide Immunization Programs in Low Income Countrie
  • Collaborative Research: Ecological and Evolutionary Impacts of Disrupted Transmission on Host-microbiome Associations
  • Models to Support Decision Making for Measles and Rubella Vaccination Planning
  • The uninvadable microbiome: towards a persistently protective microbiom

Matthew Salganik

  • Creating an Open Review Toolkit for Academic Books
  • The Future of Families and Child Wellbeing Challenge: A Scientific Mass Collaboration to Improve the Lives of Disadvantaged Children in the United States
  • Spokes: MEDIUM: NORTHEAST: Collaborative Research: Data Science Foundry: A Collaborative Platform for Computational Social Science
  • 2019 Summer Institute on Computational Social Science

Brandon Stewart

  • Collaborative Research: Analytical Tools for Text Based Social Data Integration
  • Computational Measures of Engagement Across Difference in Online Courses
  • Do Online Video Recommendation Algorithms Increase Affective Polarization?

Yu Xie

  • Heterogeneous Treatment of Effects in Demographic Research
  • Travel Awards to the RC28 Princeton University Meeting for Underrepresented Student Populations

Faculty Members