. Author manuscript; available in PMC: 2018 Mar 1.

Published in final edited form as: J R Stat Soc Series B Stat Methodol. 2016 Apr 14;79(2):573–587. doi: 10.1111/rssb.12177

Table 1.

Comparison of the NPMLE and Fine and Gray methods in the estimation of β₁₁ under proportional subdistribution hazards models^†

		NPMLE				FG
Censoring	n	Bias	SE	SEE	CP	Bias	SE	SEE	CP	RE
50%	100	−0.004	0.396	0.388	0.948	−0.002	0.401	0.394	0.954	1.03
	200	0.000	0.270	0.267	0.951	−0.008	0.272	0.276	0.946	1.01
	500	−0.001	0.162	0.153	0.945	−0.003	0.162	0.164	0.953	1.00
40%	100	−0.006	0.389	0.397	0.944	−0.001	0.409	0.412	0.965	1.11
	200	−0.003	0.263	0.267	0.942	−0.008	0.278	0.273	0.954	1.12
	500	−0.008	0.161	0.163	0.942	0.001	0.169	0.167	0.958	1.10
25%	100	−0.001	0.385	0.385	0.949	−0.001	0.413	0.408	0.956	1.15
	200	0.001	0.257	0.264	0.957	0.006	0.270	0.272	0.949	1.10
	500	0.006	0.161	0.158	0.958	0.005	0.174	0.176	0.948	1.17

^†

Bias and SE are the bias and standard error of the parameter estimator; SEE is the mean of the standard error estimator; CP is the coverage probability of the 95% confidence interval; RE is the variance of FG over that of the NPMLE. Each entry is based on 10,000 replicates.