Table 3:

Summary of simulation results (negative binomial regression) with jump to reference control-based imputation.

		Full Data			Imputation
Parameter	True	Mean	SD	MSE	Mean	SD	SE	MSE
n = 200, non-informative censoring
α	1.000	1.0158	0.1382	0.0193	1.0036	0.1732	0.1686	0.0300
β 0	1.609	1.5928	0.1127	0.0130	1.5970	0.1241	0.1245	0.0156
β 1	−0.500	−0.2844	0.1632	0.0266	−0.2724	0.0943	0.0955	0.0090
β 2	0.500	0.5042	0.1664	0.0277	0.5045	0.1859	0.1825	0.0346
n = 400, non-informative censoring
α	1.000	1.0175	0.0965	0.0096	1.0111	0.1227	0.1190	0.0152
β 0	1.609	1.6007	0.0786	0.0062	1.6078	0.0903	0.0867	0.0082
β 1	−0.500	−0.2823	0.1138	0.0130	−0.2736	0.0653	0.0663	0.0043
β 2	0.500	0.4960	0.1097	0.0121	0.4935	0.1276	0.1279	0.0163
n = 200, informative censoring
α	1.000	1.0989	0.1389	0.0291	1.0575	0.1861	0.1848	0.0379
β 0	1.609	1.5934	0.1111	0.0124	1.3821	0.1249	0.1297	0.0631
β 1	−0.500	−0.2064	0.1670	0.0279	−0.2873	0.1047	0.1060	0.0175
β 2	0.500	0.4966	0.1714	0.0294	0.5256	0.1931	0.1957	0.0379
n = 400, informative censoring
α	1.000	1.1082	0.1000	0.0217	1.0736	0.1326	0.1316	0.0230
β 0	1.609	1.6054	0.0807	0.0065	1.4010	0.0957	0.0911	0.0487
β 1	−0.500	−0.2181	0.1157	0.0133	−0.2939	0.0743	0.0738	0.0110
β 2	0.500	0.5023	0.1207	0.0146	0.5302	0.1419	0.1371	0.0211

Mean, sample average of the parameter estimates; SD, sample standard deviation of the parameter estimates; SE, sample average of the standard error estimates; MSE, mean-squared error.