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Mijke Rhemtulla


  • Ph.D., Developmental Psychology, University of British Columbia, 2010
  • M.A., Developmental Psychology, University of British Columbia, 2005
  • B.A., Psychology, University of Alberta, 2002


Mijke Rhemtulla recently moved from the psychological methods group at the University of Amsterdam to take up an academic appointment in the Department of Psychology. She received her doctorate in psychology from the University of British Columbia, where she studied early language and concept development. She was a postdoctoral fellow at the Center for Research Methods and Data Analysis at the University of Kansas before becoming an assistant professor at the University of Amsterdam.

Research Focus

Structural equation modeling (SEM) is gaining traction across disciplines of psychology as the most versatile and powerful analytic tool available to examine psychological theories. Dr. Rhemtulla develops and studies methods and models within the SEM framework, focusing on practical issues such as how to fit models to ordinal and incomplete data, how to optimize planned missing data designs for SEM models, and how to use item parcels to minimize bias. She also studies theoretical problems, such as how to interpret latent variable representations of psychological constructs, and what theoretical implications arise from competing (e.g., network) models of psychological constructs. 

Selected Publications

Schott, E., Rhemtulla, M., & Byers-Heinlein, K. (in press). Should I test more babies? Solutions for transparent data peeking. Infant Behavior and Development. 

Savalei, V., & Rhemtulla, M. (2017). Normal theory two-stage estimator for models with composites when data are missing at the item level. Journal of Educational and Behavioral Statistics, 42, 405-431.

Rhemtulla, M., & Hancock, D. (2016). Planned missing data designs for educational research. Educational Psychologist, 51, 305-316.

Rhemtulla, M. (2016). Population performance of SEM parceling strategies under measurement and structural model misspecification. Psychological Methods, 21, 348-368.

Rhemtulla, M., Fried, E. I., Aggen, S. H., Tuerlinckx, F., Kendler, K., & Borsboom, D. (2016). Network analysis of substance abuse and dependence symptoms. Drug and Alcohol Dependence, 161, 230-237.

Rhemtulla, M., Savalei, V., & Little, T. D. (2016). On the asymptotic relative efficiency of planned missingness designs. Psychometrika, 81, 60-89.

Rhemtulla, M., van Bork, R., & Borsboom, D. (2015). Calling models with causal indicators measurement models implies more than they can deliver. Measurement, 13, 59-62.

Rhemtulla, M., Jia, F., Wu, W., & Little, T. D. (2014). Planned missing designs to optimize the efficiency of latent growth parameter estimates. International Journal of Behavioral Development, 38, 5, 423-434.

Rhemtulla, M., Brosseau-Liard, P., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under sub-optimal conditions. Psychological Methods, 17, 354-373.


Dr. Rhemtulla teaches Structural Equation Modeling (PSC 205C), Measurement (PSC 104 and 205E), and Intro/Advanced Statistical Methods for Psychology (103B and 204A). 

She has previously taught courses in Multivariate Analysis and Missing Data.


Dr. Rhemtulla has received awards and fellowships from the European Research Council, the Social Sciences and Humanities Granting Council of Canada, and the National Sciences and Engineering Granting Council of Canada.