ALBERT MAYDEU OLIVARES

Structural Equation Modeling and Item Response Theory (SEM&IRT)

ORCID Research Profile

ALBERT MAYDEU OLIVARES

Position: Full Professor

Research team

 

Noemi Pereda Beltran

Associate Professor

npereda (at) ub.edu

 

David Gallardo Pujol

Associate Professor

david.gallardo (at) ub.edu

Contact details

 

Prof. Albert Maydeu Olivares

Department of Psicologia Clínica i Psicobiologia

Faculty of Psychology, Passeig Vall d’Hebron 171

08035 Barcelona (Spain)

+34 933125133

amaydeu (at) ub.edu

www.ub.edu/gdne/…

Research Interests

 

His research interest focus on structural equation modeling and item response theory (IRT), and more generally in developing new quantitative methods. His early research focused on social problem solving (how individuals solve real life problems) and optimism. He is probably best known for his research on goodness of fit tests for very sparse categorical data (with applications to educational testing), and models for preference and choice (with applications to marketing but also to personnel selection). His most recent work focuses on goodness of fit testing of structural equation models, statistical models to overcome common method bias, and statistical modeling of faking in personnel selection

Highlighted publications

 

· Maydeu-Olivares, A. (2017). Assessing the Size of Model Misfit in Structural Equation Models. Psychometrika, 82(3), 533–558. http://doi.org/10.1007/s11336-016-9552-7

 

· Maydeu-Olivares, A. (2017). Maximum likelihood estimation of structural equation models for continuous data: Standard errors and goodness of fit. Structural Equation Modeling, 24(3), 383–394. http://doi.org/10.1080/10705511.2016.1269606

 

· Steenkamp, JBEM & Maydeu-Olivares, A. (2015). On the temporal stability of consumer dispositions: evidence from a twelve-year longitudinal study, 2002-2013. Journal of Marketing Research, 52, 287-308.

 

· Maydeu-Olivares, A. (2013). Goodness-of-fit assessment of item response theory models. Measurement, 11, 71-101.

 

· Brown, A. & Maydeu-Olivares, A. (2013). How IRT can solve problems of ipsative data in forced-choice questionnaires. Psychological Methods, 18, 36-52.