Michel Regenwetter, Professor

19962019
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Personal profile

Professional Information

Individual preferences fluctuate over time and differ among people. Few models of utility and decision making attempt to capture this fundamental fact explicitly. Prof. Regenwetter's primary goal is to model, measure, and predict preference and choice behavior when it is allowed to vary. Random utility models are designed as a modeling language to capture and quantify the ubiquitous variability in choice and preference behavior. Prof. Regenwetter's primary interests can be categorized as falling within three paradigms: probabilistic measurement, social choice, and preference evolution over time. Probabilistic measurement theory reformulates axiomatic measurement structures (e.g., in decision theory) in a probabilistic framework and thereby makes them empirically (and statistically) testable. Social choice theory is the theory of aggregating individual preferences or choices into a social ordering or choice. Dr. Regenwetter's interest in social choice is behavioral. Using random utility models as measurement tools, he evaluates and compares competing social choice functions on empirical data of various kinds. Dr. Regenwetter studies preference change over time via stochastic process models in which random utilities are indexed by continuous time.

Research Interests

Decision Making
Mathematical Psychology
Behavioral Social Choice
Behavioral Economics

Professional Information

  • Fellow, Association for Psychological Science
  • Young Investigator Award, Society for Mathematical Psychology

Teaching

Models of Decision and Choice
Testing Theories of Decision
Foundations of Behavioral Social Choice Research
Introduction to Statistics
Psychological Statistics

Honors & Awards

Fellow, Association for Psychological Science
Young Investigator Award, Society for Mathematical Psychology

Office Address

435

Office Phone

Education/Academic qualification

Mathematical Behavioral Sciences, Ph.D., University of California at Irvine

Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

Statistical Models Medicine & Life Sciences
Politics Medicine & Life Sciences
Social Choice Mathematics
Probabilistic Model Mathematics
Voting Mathematics
Behavioral Research Medicine & Life Sciences
Ranking Mathematics
Choice Models Mathematics

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Research Output 1996 2019

QTEST 2.1: Quantitative testing of theories of binary choice using Bayesian inference

Zwilling, C. E., Cavagnaro, D. R., Regenwetter, M., Lim, S. H., Fields, B. & Zhang, Y., Aug 2019, In : Journal of Mathematical Psychology. 91, p. 176-194 19 p.

Research output: Contribution to journalArticle

Binary Choice
Statistical Models
Bayesian inference
Probabilistic Model
Dacarbazine

The construct-behavior gap revisited: Reply to Hertwig and Pleskac (2018)

Regenwetter, M. & Robinson, M. M., Apr 2019, In : Psychological review. 126, 3, p. 451-454 4 p.

Research output: Contribution to journalComment/debate

Behavioral Research
Psychology

The 'Paradox' of Converging Evidence

Davis-Stober, C. P. & Regenwetter, M., Jan 1 2019, In : Psychological review.

Research output: Contribution to journalArticle

Individuality
Psychological Theory
Social Psychology
Statistical Data Interpretation
Health Services Needs and Demand

Towards Meaningful Inferences From Attitudinal Thermometer Ratings

Regenwetter, M., Hsu, Y. F. & Kuklinski, J. H., Jan 1 2019, In : Decision.

Research output: Contribution to journalArticle

Thermometer
Thermometers
Social Psychology
Public Sector
Semiorder

Tutorial on removing the shackles of regression analysis: How to stay true to your theory of binary response probabilities

Regenwetter, M. & Cavagnaro, D. R., Apr 2019, In : Psychological Methods. 24, 2, p. 135-152 18 p.

Research output: Contribution to journalArticle

Regression Analysis
Statistical Data Interpretation
Psychology
Research
Direction compound