18  Compare results

Summary of model results
OR Beta-coef coef-SE CI (2.5 %) CI (97.5 %) p-value
Crude (no adjustment) 2.08 0.73 0.05 0.63 0.84 < 2e-16
PS (no proxies) 1.98 0.68 0.04 0.61 0.76 < 2e-16
hdPS 1.52 0.42 0.04 0.35 0.49 < 2e-16
Pure LASSO 1.51 0.41 0.04 0.34 0.49 < 2e-16
Hybrid (hdPS, then LASSO) 1.55 0.44 0.04 0.36 0.51 < 2e-16
Super learner (GLM, LASSO, MARS) 1.60 0.47 0.04 0.39 0.54 < 2e-16
TMLE (GLM, LASSO, MARS in SL) 1.57 0.45 0.05 0.34 0.55 < 2e-16
TMLE (only GLM in SL) 1.55 0.44 0.06 0.33 0.55 2.7e-15
  • PS is the result from the propensity score approach that did not include any proxies.
  • Results from this approach is somewhat different than other approaches.
  • More detailed results from simulations are available elsewhere (Karim 2023).

Most hdPS, ML extensions (pure, SL or TMLE) and hybrids perform similarly (ORs between 1.52-1.6)