- Causal inference : design and analysis of randomized experiments and observational studies accounting for complications such as interference among experimental units, non-compliance to assigned treatments, and principal strata.
- Experimental design : design and analysis of fractional factorial designs with complex aliasing, statistical process and quality control, optimum designs, computer experiments.
- Bayesian statistics : Bayesian model building, posterior predictive checks, multiple comparison procedures, MCMC methods, Hamiltonian Monte Carlo, missing data.
- Algebraic statistics : application of algebraic techniques to experimental design.
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