TABLE 1.

Performance of IPW estimator of the difference in RMTL in simulation studies, τ = 365 days

Proportional subdistribution hazards, ν = −22.63 days at τ = 365 days
Sample size	Exposed	Censoring	Bias, days	Rel bias	RMSE, days	Rel SE	Coverage
500	25%	10%	−0.026	0.001	14.269	1.262	0.984
		25%	0.231	−0.010	15.046	1.224	0.982
	50%	10%	0.118	−0.005	12.568	1.173	0.976
		25%	0.197	−0.009	13.179	1.146	0.974
1000	25%	10%	0.134	−0.006	10.153	1.248	0.984
		25%	0.424	−0.019	10.455	1.237	0.981
	50%	10%	−0.319	0.014	8.949	1.158	0.977
		25%	−0.182	0.008	9.267	1.146	0.974
Nonproportional subdistribution hazards, ν = 8.03 days at τ = 365 days
Sample size	Exposed	Censoring	Bias, days	Rel bias	RMSE, days	Rel SE	Coverage
500	25%	10%	0.721	0.090	16.702	1.215	0.980
		25%	0.759	0.095	17.433	1.196	0.978
	50%	10%	0.716	0.089	13.291	1.206	0.981
		25%	0.616	0.077	14.163	1.163	0.980
1000	25%	10%	0.344	0.043	11.679	1.219	0.982
		25%	0.264	0.033	12.070	1.213	0.980
	50%	10%	0.359	0.045	9.495	1.186	0.979
		25%	0.379	0.047	9.872	1.174	0.977

Note: To assess the IPW method, we generated competing risks data dependent on a binary covariate A and covariates Z. We obtained ν, the true adjusted difference in RMTL between A = 1 and A = 0 at τ = 365 days with a counterfactual approach in a sample of n = 1,000,000.

Abbreviations: IPW, inverse probability weighted; Rel bias, mean bias relative to true parameter; Rel SE, mean estimated standard error/Monte Carlo empirical error; RMSE, root of mean squared error; RMTL, restricted mean time lost.