TABLE A6.

Single Confounder Inclusion: simulation results for λ(X_j) using nonparametric estimation with n = 2000;

Variable	1	2	3	4	5
Setting 1
Truth	0.128	0.080	0.062	0.063	0.009
Estimate	0.127	0.073	0.063	0.058	0.008
Bias	0.001	0.007	−0.001	0.005	0.001
ESE	0.016	0.016	0.011	0.009	0.005
Setting 2
Truth	0.133	0.000	0.065	−0.004	0.009
Estimate	0.131	0.000	0.066	−0.003	0.008
Bias	0.001	0.000	−0.001	−0.001	0.001
ESE	0.016	0.004	0.011	0.005	0.005
Setting 3
Truth	0.189	0.065	−0.012	0.142	0.016
Estimate	0.187	0.066	−0.010	0.129	0.015
Bias	0.001	−0.001	−0.002	0.013	0.002
ESE	0.019	0.011	0.011	0.018	0.008
Setting 4
Truth	0.124	0.073	0.063	0.061	0.007
Estimate	0.125	0.070	0.062	0.056	0.008
Bias	−0.002	0.004	0.001	0.005	0.000
ESE	0.016	0.016	0.011	0.010	0.006

ESE = empirical standard error (standard deviation of estimates across the 1,000 replications)