[1] CAUSATION: Causal inference (including covariate selection, double robust estimation, double/debiased machine learning), quasi-experimental designs (matching designs, propensity score designs, regression discontinuity designs, interrupted time series designs), causal diagrams, structural causal models, causal mediation analysis, causal decomposition analysis (for disparity research), time-varying treatment regimes.
[2] REPLICATION: Causal replication designs & reproducibility, design replication studies (within-study comparisons) for evaluating quasi-experimental designs.
[3] SURVEY DESIGN: Factorial survey, experimental vignette designs.