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Jeremy Freese

Jeremy Freese


I am interested broadly in the relationship between social differences and individual differences, and between social advantage and embodied advantage.  This includes work differences in physical health, cognitive functioning, health behaviors, and the role of differential utilization of knowledge and innovations toward producing differences.  I am co-leader of the Health Disparities Working Group for the Stanford Center for Population Health Sciences.


I am part of ongoing efforts to better integrate biological and social science thinking.  I have worked on how behavioral and molecular genetic information can be used to complement and elaborate our understanding of the consequences of social environments.  I have also done work on the application of evolutionary biological reasoning to human behavior and social arrangements.


I am co-author of a book on discrete-choice-type models, which is now in its third edition and is used in many graduate classes in the social sciences.  For this book, I am also co-author of a widely-used suite of add-on commands to the software package Stata that facilitates the interpretation of model results.  I teach statistics and data analysis to graduate students here at Stanford.


I also do other work on improving the practice and conceptualization of social research.  This includes projects on best practices for survey research, how to improve participation in social surveys, and how to think more clearly about complex causal processes.  I am also involved in some science studies research regarding the rise of meta-analysis and open science.


I am co-PI of three major social science “public goods” projects.  Time-Sharing Experiments in the Social Sciences (NSF) promotes experimentation in the social sciences by soliciting proposals for survey experiments and fielding selected proposals for free using an Internet-based nationally representative sample.  General Social Survey (NSF) is the most-used survey to study trends in social characteristics and attitudes in the United States, and, as part of the International Social Survey Programme, it is also the most-used survey for comparing US public opinion to other countries.  Wisconsin Longitudinal Study (NIA) is one of the longest-running population-based survey studies in the US, and I am a central member of the team that is integrating Genome-Wide Association Study (GWAS) data into this study.