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Yaremych (2)

I am a fourth-year Quantitative Methods Ph.D. candidate in the Department of Psychology and Human Development, and a National Science Foundation (NSF) graduate research fellow.

Methodologically, my primary line of research focuses on developing practical tools and substantively useful insights pertaining to multilevel modeling. I have published and presented work which illuminates best practices for centering multicategorical predictors in multilevel models, and interpreting their effects. Currently in my NSF-funded work, I am studying approaches for diagnosing and mitigating the harmful effects of collinearity in multilevel data. In another project, I am investigating the advantages of a Bayesian approach for modeling three-way cross-classified multilevel data.

Substantively, I am particularly interested in applying advanced statistical methods to questions in family and health psychology. I have also conducted work investigating the use of virtual reality for enhancing behavioral measurement and assessment in psychology.