Milica Miočević

Research Areas:

Quantitative Psychology & Modelling

Research Summary:

My research interests revolve around mediation analysis and Bayesian methods applied to social science research. More specifically, I have three research lines that focus on: 1) optimal methods for using historical data and pilot studies to create informative prior distributions for Bayesian mediation analysis, 2) methods for synthesizing findings about the mediated effect in the presence of important between-study differences (e.g., samples from different populations), and 3) mediation analysis in Single Case Experimental Designs (SCEDs). These methods have broad applications in psychology and related fields.

I am accepting graduate student applications for the Fall 2020 year (due on December 1st, 2019).
 

Selected References:

Miočević, M., Levy, R., & Savord, A. (2020). The Role of Exchangeability in Sequential Updating of Findings from Small Studies and the Challenges of Identifying Exchangeable Data Sets. In R. Van de Schoot & M. Miočević (Eds.), Small sample size solutions: A guide for applied researchers and practitioners: Routledge.

Smid, S. C., McNeish, D., Miočević, M., & van de Schoot, R. (2019). Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review. Structural Equation Modeling: A Multidisciplinary Journal, 1-31.

Miočević, M., Gonzalez, O., Valente, M. J., & MacKinnon, D. P. (2018). A tutorial in Bayesian potential outcomes mediation analysis. Structural Equation Modeling: A Multidisciplinary Journal, 25(1), 121-136.

Miočević, M., MacKinnon, D. P., & Levy, R. (2017). Power in Bayesian Mediation Analysis for Small Sample Research. Structural Equation Modeling: A Multidisciplinary Journal, 1-18.

Miočević, M., O’Rourke, H. P., MacKinnon, D. P., & Brown, H. C. (2017). Statistical properties of four effect-size measures for mediation models. Behavior Research Methods, 1-17.