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Research Areas:

Quantitative & Modelling

Research Summary:

Professor Falk鈥檚 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) methods for modeling or detecting atypical responding on Likert-type items; (2) methods for quantifying model complexity and conducting model selection; (3) semi- and non-parametric item response models for when common parametric assumptions are violated; (4) appropriate ways of handling of missing and non-normal data; and (5) interval estimation techniques for functions of model parameters (e.g., indirect effect in mediation analysis models).

Professor Falk will consider PhD student applications for Fall 2025.

Selected References:

Recent/Representative Statistical Software

* Denotes student/mentee co-author

*Ilagan, M. J., & Falk, C.F. (2024). detranli: DEtection of RANdom LIkert-type responses. R package available from GitHub:

Falk, C.F. (2024). EMgaussian: Expectation-Maximization algorithm for multivariate normal (Gaussian) with missing data. R package available from CRAN,

Falk, C.F., *Vogel, T., *Hammami, S., & Mio膷evi膰, M. (2021). multilevelmediation: Utility functions for multilevel mediation analysis in R. R package available from CRAN,

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/Representative Publications

* Denotes student/mentee co-author

Falk, C. F., *Huang, A., & *Ilagan, M. J. Unsupervised survey bot detection: In search of high classification accuracy. Preprint:

*Chen, L., Mio膷evi膰, M., & Falk, C. F. (in press). Tackling challenges in data pooling: missing data handling in latent variable models with continuous and categorical indicators. Structural Equation Modeling: A Multidisciplinary Journal.

*Ilagan, M.J., & Falk, C. F. (2024). Model-agnostic unsupervised detection of bots in a Likert-type questionnaire. Behavior Research Methods, 56, 5068-5085.

*Somer, E., Falk, C. F., & Mio膷evi膰, M. (2024). Comparing factor score approaches to SEM in multigroup models with small samples. Structural Equation Modeling: A Multidisciplinary Journal, 31, 310-328.

Falk, C. F., *Vogel, T. A., *Hammami, S., & Mio膷evi膰, M. (2024). Multilevel mediation analysis in R: A comparison of resampling and Bayesian approaches. Behavior Research Methods, 56, 750-764.

Falk, C.F., & Muthukrishna, M. (2023). Parsimony in model selection: Tools for assessing fit propensity. Psychological Methods, 28, 3247-3255.

• Equal first-authorship
• Won research award (2023) from the

*Starr, J., & Falk, C.F. (2023). A comparison of latent variable and psychological network models in mental and physical health symptom data: Common output metrics and factor structure. Quality of Life Research, 32, 3247-3255.

Falk, C.F., & Fischer, F. (2022). More flexible response functions for the PROMIS physical functioning item bank by application of a monotonic polynomial approach. Quality of Life Research, 31, 37-47.

Falk, C.F., & Feuerstahler, L.M. (2022). On the performance of semi- and non-parametric item response functions in computer adaptive tests. Educational and Psychological Measurement, 82, 57-75.

*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.

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.

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

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 from the

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. .

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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