Richard Gonzalez
Center Director, Research Center for Group Dynamics, Institute for Social Research
Co-Director, BioSocial Methods Collaborative
Amos N Tversky Collegiate Professor, Psychology and Statistics, LSA
Professor of Integrative Systems and Design, College of Engineering
| E-mail: | Email Richard Gonzalez |
| Address: | Research Center for Group Dynamics Institute for Social Research University of Michigan 426 Thompson Street Ann Arbor, Michigan 48106 |
| Phone: | 734-647-6785 |
About Me
I received my PhD in 1990 from Stanford University in Psychology. I worked with Phoebe Ellsworth studying psychology and law and with Amos Tversky studying mathematical modeling and judgment and decision making. I spent seven years at the University of Washington’s Psychology department, a sabbatical year at Princeton University, and have been at the University of Michigan’s Psychology department since 1997. More about me >>
Research
My research interests focus on judgment and decision making (JDM). Given that so many topics in psychology are related to JDM it makes it look as though I work on many different topics. Actually, I see a simple theme across all my research. I am interested in how people make judgments and what influences their decisions and choices. More about Research >>
People
I’ve been fortunate to work with amazing colleagues, coauthors, collaborators, and students throughout my career. Read about People >>
Teaching
- Theories of Social Psychology
- General Linear Modeling Course
- Multivariate Statistics
- Generalized Linear Modeling Course
- Structural Equations Modeling Course
- Statistics Animation Page
- Design Science PhD Program
Recent Posts
Reviewing the endowment-contrast model of happiness and well-being
If we have an amazing experience, such as an excellent meal or a the dream vacation, when does it become part of our endowment (i.e., another positive tick mark that we accumulate)or a source of comparison against which other relevant experiences are judged and contrasted? In the former case, the experience makes us happier, but in the latter case it can diminish our ability to enjoy future events.
Extending prospect theory to cases where probabilities are not known
We extend cumulative prospect theory to the domain of events, investigate two sources on nonlinearity on decision weights, and propose a two stage model of choice.
Standard errors for parameters in dyadic models
We show how to derive standard errors for a few basic models in dyadic data analysis. The chapter was written for Michael Browne’s festschrift.
Analyzing multivariate dyadic data for exchangeable dyads
This was our first paper on dyadic analysis. In retrospect, one of our main contributions was more pedagogical in that we showed how to get solid intuition about dyadic data and presented a framework in which to derive estimates and their standard errors. The framework illuminated several aspects of dyadic data, including why a correlation of dyadic means is sometimes difficult to interpret. Our results are identical to multilevel models using maximum likelihood estimation.
