May 28, 2020
Hosted by the Center for Social & Behavioral Science
This workshop begins with an introduction to causal inference by CSBS Director Brent Roberts.
Bayesian Statistics for Social & Behavioral Scientists
Given by Dr. David Kaplan, the Patricia Busk Professor of Quantitative Methods in the Department of Educational Psychology at the University of Wisconsin – Madison, this workshop introduced social and behavioral scientists to the basic elements of Bayesian statistics and illustrated why the Bayesian perspective provides a powerful alternative to the frequentist perspective
Structural Equation Modeling workshop
Given by Dr. Daniel Briley, Assistant Professor of psychology at the University of Illinois, and Dr. Ross Jacobucci, Assistant Professor of psychology at the University of Notre Dame, this hands-on workshop helped attendees learn about SEM techniques and apply them to their own research problems.
The workshop concluded with a discussion with panel members listed below:
- Jacob Bowers, Associate Professor of Political Science and Statistics, University of Illinois.
- Jonathan Livengood, Associate Professor of Philosophy, University of Illinois.
- Lucia Petito, Assistant Professor of Preventive Medicine (Biostatistics), Northwestern University.
- Rodrigo Pinto, Assistant Professor of Economics, University of California Los Angeles.
- Felix Thoemmes, Associate Professor of Human Development, Cornell University
Video playback of the workshop is now available on Media Space, segmented accordingly:
Jonathan Livengood, Associate Professor of Philosophy at University of Illinois, introduced the formalism of graphical causal models and how to interpret them, discussed some results in causal search, as well as the problem of mixed populations.
Lucia Petito, Assistant Professor of Preventive Medicine (Biostatistics) at Northwestern University, introduced participants to the estimation of intention-to-treat and per-protocol effects in randomized trials with survival outcomes, and how to extend these concepts to research done in “found” data using the target trial concept.
Jacob Bowers, Associate Professor of Political Science and Statistics at University of Illinois, showed how a testing-based approach to causal inference can be used to complement estimation-based approaches in complex but common situations. This can include when an experiment occurs in thousands of sites, and policymakers’ interest may lie in detecting effects in specific sites rather than in estimating an average effect within each site.
Felix Thoemmes, Associate Professor of Human Development at Cornell University, discussed the history of causal thinking in the field of psychology, juxtaposed with developments outside the field, and how current examples from psychological research could be improved with considerations of causal effects.
Rodrigo Pinto, Assistant Professor of Economics at the University of California Los Angeles, addressed economic incentives, human behavior, and the design of social experiments and showed how instrumental variables can be applied to examine some important social experiments that fight poverty.
Powerpoint slides of each presentation are also available to view and to download.