Carl F. Falk

Academic title(s): 

Assistant Professor


Contact Information:


Office: 2001 McGill College, 753
Phone: 514.398.6133
Email: carl.falk[at]


Mailing Address:
Department of Psychology
2001 McGill College, 7th floor
Montreal, QC
H3A 1G1


Carl F. Falk

Research Areas:

Quantitative & Modelling

Research Summary:

Professor Falk’s research focuses mainly on the development, computer programming, and testing of latent variable models and related statistical methods, spanning across item response theory, structural equation modeling, and multilevel modeling. This research is envisioned as having potential broad applications across psychology and other social science disciplines (e.g., education, sociology, health outcomes). Recent examples include: (1) models for measuring psychological constructs in the presence of response styles; (2) semi- and non-parametric item response models for when common parametric assumptions are violated; (3) appropriate ways of handling of missing and non-normal data in structural equation modeling; and (4) interval estimation techniques for functions of model parameters (e.g., indirect effect in mediation analysis models).

Selected References:

Representative Statistical Software

* Denotes student co-author

Falk, C. F., *Vogel, T., *Hammami, S., & Miočević, M. (in development). multilevelmediation: Utility functions for multilevel mediation analysis in R. R package will be available from GitHub:

Falk, C.F. & Muthukrishna, M. (2020). ockhamSEM: Tools for studying fit propensity in structural equation modeling. R package available from GitHub:

Falk, C.F. (2020). mpirt: Functions for estimating monotonic polynomial item response models using rpf and OpenMx. R package available from GitHub:

Forked version of lavaan for computing (robust) likelihood-based confidence intervals:

Falk, C.F. & Biesanz, J.C. (2013). P-value calculator for mediation analysis. Available from

Falk, C.F. & Biesanz, J.C. (2013). Confidence interval calculator for mediation analysis. Available from

Falk, C.F. & Joe, H. (2012). pln: Polytomous logit-normit (graded logistic) model estimation. R package available from

Recent and Representative Publications

* Denotes student co-author

Falk, C.F., & Muthukrishna, M. (in press). Parsimony in model selection: Tools for assessing fit propensity. Psychological Methods. Accepted version:  - Equal first-authorship

Falk, C.F., & Fischer, F. (in press). More flexible response functions for the PROMIS physical functioning item bank by application of a monotonic polynomial approach. Quality of Life Research.

Falk, C.F., & Feuerstahler, L.M. (in press). On the performance of semi- and non-parametric item response functions in computer adaptive tests. Educational and Psychological Measurement.

*Starr, J., Falk, C.F., Monroe, S., & Vachon, D.D. (2021). A comparison of limited information fit statistics for a response style MIRT model. Multivariate Behavioral Research, 56, 687-702.

Hwang, H., *Cho, G., Jung, K., Falk, C.F., Flake, J., Jin, M.J., & Lee, S.H. (2021). An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis. Psychological Methods, 26, 273-294.

Falk, C.F., & *Ju, U. (2020). Estimation of response styles using the multidimensional nominal response model: A tutorial and comparison with sum-scores. Frontiers in Psychology: Quantitative Psychology and Measurement, 11:72, 1-17.

*Hong, S.E., Monroe, S., & Falk, C.F. (2020). Performance of person-fit statistics under model misspecification. Journal of Educational Measurement, 57, 423-442.

Falk, C.F. (2020). The monotonic polynomial graded response model: Implementation and a comparative study. Applied Psychological Measurement, 44, 465-481.

*Ju, U., & Falk, C.F. (2019). Modeling response styles in cross-country self-reports: An application of a multilevel multidimensional nominal response model. Journal of Educational Measurement, 56, 169-191.

Falk, C.F. (2018). Are robust standard errors the best approach for interval estimation with non-normal data in structural equation modeling? Structural Equation Modeling: A Multidisciplinary Journal, 25, 244-266.  - Won research award (2018) from the Quantitative Methods Section of the Canadian Psychological Association

Falk, C.F., & Monroe, S. (2018). On Lagrange Multiplier tests in multidimensional item response theory: Information matrices and model misspecification. Educational and Psychological Measurement, 78, 653-678.

Marcoulides, K.M., & Falk, C.F. (2018). Model specification searches in structural equation modeling with R. Structural Equation Modeling: A Multidisciplinary Journal, 23, 484-491.

Falk, C.F., & Cai, L. (2016). A flexible full-information approach to the modeling of response styles. Psychological Methods, 21, 328-347.

Falk, C.F., & Cai, L. (2016). Maximum marginal likelihood estimation of a monotonic polynomial generalized partial credit model with applications to multiple group analysis. Psychometrika, 81, 434-460.


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