Table 1.

Error in Treatment Parameter Estimation 100-Replication Monte Carlo Simulations by Strength of Correlation (Endogeneity)

	Median [inter-95% range] treatment parameter estimation error, by correlation scenario
	ρ ~50%	ρ ~25%	None
Endogenous switching survival model
N=1000	0.12 [−0.42,0.77]	0.14 [−0.35,0.62]	0.13 [−0.47,0.65]
N=5000	−0.03 [−0.22,0.20]	−0.07 [−0.25,0.18]	−0.05 [−0.27,0.18]
N=10,000	0.01 [−0.20,0.22]	−0.03 [−0.17,0.18]	−0.05 [−0.17,0.15]
Two-stage residual inclusion
N=1000	0.14 [−0.42,0.87]	0.13 [−0.31,0.65]	0.10 [−0.41,0.67]
N=5000	−0.05 [−0.37,0.20]	−0.03 [−0.32,0.16]	−0.03 [−0.31,0.16]
N=10,000	−0.06 [−0.26,0.19]	−0.05 [−0.22,0.16]	−0.04 [−0.20,0.15]
Regression weighted by inverse probability (propensity score)
N=1000	1.30 [0.95,1.59]	0.69 [0.20,1.00]	−0.04 [−0.48,0.44]
N=5000	1.25 [1.10,1.43]	0.61 [0.43,0.81]	−0.01 [−0.21,0.18]
N=10,000	1.23 [1.12,1.33]	0.60 [0.46,0.75]	0.00 [−0.13,0.14]
Regression stratified by propensity score
N=1000	1.26 [0.91,1.52]	0.65 [0.18,1.01]	−0.01 [−0.47,0.53]
N=5000	1.20 [1.07,1.32]	0.57 [0.43,0.77]	−0.01 [−0.20,0.21]
N=10,000	1.20 [1.08,1.27]	0.59 [0.44,0.72]	−0.01 [−0.12,0.15]
Weibull hazard with no endogeneity correction
N=1000	1.07 [0.83,1.33]	0.50 [0.23,0.76]	0.02 [−0.25,0.34]
N=5000	0.99 [0.87,1.08]	0.42 [0.29,0.54]	−0.01 [−0.16,0.12]
N=10,000	1.00 [0.90,1.07]	0.44 [0.34,0.52]	0.00 [−0.04,0.03]