Table 2.

Results for case 2 in which a chi-squared distribution with two degrees of freedom was created for the outcome data with three repeated measures.

			α = 0.3			α = 0.7
n	% Censor		LOD/2	MLE	Quantile	LOD/2	MLE	Quantile
100	10	Bias	0.0197	0.0210	−0.0008	0.0073	0.0138	0.0006
		MSE	0.0006	0.0006	0.0005	0.0003	0.0004	0.0007
		RE	1.000	0.921	1.279	1.000	0.741	0.413
	20	Bias	0.0186	0.0221	−0.0001	−0.0032	0.0166	0.0003
		MSE	0.0006	0.0007	0.0005	0.0003	0.0005	0.0007
		RE	1.000	0.823	1.194	1.000	0.588	0.424
	30	Bias	0.0192	0.0231	−0.0020	−0.0155	0.0195	−0.0022
		MSE	0.0006	0.0007	0.0005	0.0007	0.0006	0.0008
		RE	1.000	0.884	1.324	1.000	1.087	0.873
	40	Bias	0.0169	0.0236	−0.0057	−0.0477	0.0216	−0.0036
		MSE	0.0010	0.0008	0.0006	0.0044	0.0007	0.0008
		RE	1.000	1.261	1.679	1.000	6.211	5.668
500	10	Bias	0.0194	0.0207	−0.0010	0.0062	0.0127	−0.0007
		MSE	0.0004	0.0005	0.0001	0.0001	0.0002	0.0001
		RE	1.000	0.891	4.172	1.000	0.425	0.670
	20	Bias	0.0185	0.0219	−0.0017	−0.0045	0.0156	−0.0014
		MSE	0.0004	0.0005	0.0001	0.0001	0.0003	0.0001
		RE	1.000	0.742	3.859	1.000	0.274	0.609
	30	Bias	0.0192	0.0229	−0.0033	−0.0164	0.0185	−0.0031
		MSE	0.0004	0.0006	0.0001	0.0004	0.0004	0.0002
		RE	1.000	0.748	3.843	1.000	0.913	2.380
	40	Bias	0.0188	0.0234	−0.0068	−0.0415	0.0205	−0.0064
		MSE	0.0004	0.0006	0.0002	0.0021	0.0005	0.0002
		RE	1.000	0.762	2.801	1.000	4.373	10.85

^aBias - empirical bias.

^bMSE - empirical mean squared error.

^cRE - relative efficiency. These are the italicized ratios that, for each setting (n), compare the empirical MSE from the LOD/2 substitution method to the MSE from the use of MLE method or quantile regression model.