Bryan Keller

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Keller, Bryan
Assistant Professor of Applied Statistics
Department of Human Development
212-678-3277

Office:
453E GDodge

Educational Background

Ph.D., Educational Psychology, Quantitative Methods, University of Wisconsin-Madison, 2013
M.A., Educational Psychology, Quantitative Methods, University of Wisconsin-Madison, 2010
M.S., Mathematics, Binghamton University, 2002
B.S., Mathematics, Binghamton University, 2000

Scholarly Interests

My research is related to the application, development, and assessment of quantitative methods in the social and behavioral sciences. I am particularly interested in methods for causal inferences and estimation of treatment effects. In the quasi-experimental setting I have worked on propensity score methods for the analysis of non-equivalent control group designs, detection of treatment effect heterogeneity, and developed methods for variable selection. In the experimental setting I am interested in design-replication studies and permutation-based statistical tests. I find computationally intensive methods such as regression trees and resampling and reordering methods to be very useful tools in my work.

Selected Publications

Under Review:

Keller, B. (Under Review). Variable Selection for Causal Effect Estimation: Conditional Random Forest Variable Importance Under Permutation. (pdf) (R_package) (R_code)

Methods:

Chen, J. & Keller, B. (Forthcoming). Heterogeneous Subgroup Identification in Observational Studies. Journal of Research on Educational Effectiveness. (pdf) (R_code)

Keller, B., Chen, J., & Zhang, T. (Forthcoming) Heterogeneous Subgroup Identification with Observational Data: A Case Study Based on the National Study of Learning Mindsets. Observational Studies. (pdf)

Bazaldua, D. A. L., Lee, Y.-S., Keller, B., & Fellers, L. (2017). Assessing the Performance of Classical Test Theory Item Discrimination Estimators in Monte Carlo Simulations. Asia Pacific Education Review, 18: 585–598. (link)

Keller, B. & Tipton, E. (2016). Propensity score analysis in R: A software review. Journal of Educational and Behavioral Statistics, 41: 326–348. (link

Keller, B., Kim, J.-S., & Steiner, P. M. (2015). Neural networks for propensity score estimation: Simulation results and recommendations. In L. A. van der Ark, D. M. Bolt, S.-M. Chow, J. A. Douglas, & W.-C. Wang (Eds.), Quantitative psychology research. New York, NY: Springer. (pdf) (R_package) (R_code)

Kim, J.-S., Anderson, C. J., & Keller, B. (2014). Multilevel analysis of large-scale assessment data. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), A handbook of international large-scale assessment: Background, technical issues, and methods of data analysis. London: Chapman Hall/CRC Press. (pdf)

Anderson, C. J., Kim, J.-S., & Keller, B. (2014). Modeling multilevel categorical response variables. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), A handbook of international large-scale assessment: Background, technical issues, and methods of data analysis. London: Chapman Hall/CRC Press. (pdf)

Keller, B., Kim, J.-S., & Steiner, P. M. (2013). Data mining alternatives to logistic regression for propensity score estimation: Neural networks and support vector machines. Multivariate Behavioral Research, 48, 164 (Abstract). (pdf

Keller, B. (2012). Detecting treatment effects with small samples: The power of some tests under the randomization model. Psychometrika, 77, 324-338. (link) (R_code)

Kaplan, D. & Keller, B. (2011). A note on cluster effects in latent class analysis. Structural Equation Modeling, 18, 525-536. (link)

Applications:

Schwinn, T. M., Schinke, S. P., Keller, B., Hopkins, J. E. (2019). Two- and Three-Year Follow-Up from a Gender-Specific, Web-Based Drug Abuse Prevention Program for Adolescent Girls. Addictive Behaviors, 93: 86-92. (link)

Yang, J., Clarke-Midura, J., Keller, B., Baker, R. S., Paquette, L., & Ocumpaugh, J. (2018) Note-Taking and Science Inquiry in an Open-ended Learning Environment. Journal of Contemporary Educational Psychology, 55: 12–29. (link)

McCullough, A. K., Keller, B., Qiud, S., & Ewing Garber, C. (2018). Analysis of accelerometer-derived interpersonal spatial proximities: A calibration, simulation, and validation study. Measurement in Physical Education and Exercise Science, 22: 275–286. (link)

Schwinn, T. M., Schinke, S. P., Hopkins, J. E., Keller, B., & Liu, X. (2018). An online drug abuse prevention program for adolescent girls: Posttest and 1-year outcomes. Journal of Youth and Adolescence, 47: 490–500. (link)

Weishaar, T., Rajan, S., Keller, B. (2016). Probability of vitamin D deficiency by body weight and race-ethnicity. Journal of the American Board of Family Medicine, 29: 226–232. (link)

Rajan, S., Weishaar, T., Keller, B. (2016). Weight and skin color as predictors of vitamin D status: Results of an epidemiological investigation using nationally representative data. Public Health Nutrition, 12: 1–8. (link)

Teaching

  • HUDM 4125 - Statistical Inference; Fall 2014 - Fall 2017
  • HUDM 5026 - Introduction to Data Analysis and Graphics in R; Summer 2014 - present
  • HUDM 5123 - Linear Models and Experimental Design; Fall 2014 - present
  • HUDM 5133 - Causal Inference and Program Evaluation; Spring 2016 - present
  • HUDM 5150 - Capstone, Careers, and Communication; Fall 2018 - present
  • HUDM 6122 - Multivariate Analysis; Spring 2017
  • HUDM 6026 - Computational Statistics; Spring 2014 - Spring 2016

Journal Reviewing

  • Advances in Methods and Practices in Psychological Science
  • Journal of Causal Inference
  • Journal of Educational and Behavioral Statistics
  • Journal of Research on Educational Effectiveness
  • Measurement in Physical Education and Exercise Science
  • Multivariate Behavioral Research
  • Pharmaceutical Statistics
  • PLOS One
  • Psychological Methods
  • Research Synthesis Methods
  • Structural Equation Modeling: A Multidisciplinary Journal

Courses

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