Table 2.

The average (“ave”) and the sample standard errors (“std”) for various estimates, and the inference results, respectively, the average of the estimated standard deviation (“ $\widehat{\text{std}}$”) and the coverage of the estimated 95% confidence interval (“95%”), of the oracle estimator and the efficient estimator, of β in simulated example 2

		β1	β2	β3	β4	β5	β6
		1.3	−1.3	1	−0.5	0.5	−0.5
Oracle	ave	1.2999	−1.3001	1.0001	−0.4999	0.5002	−0.4999
	std	0.0023	0.0025	0.0028	0.0022	0.0023	0.0024
		0.0021	0.0020	0.0026	0.0020	0.0021	0.0023
	95%	0.9260	0.9070	0.9270	0.9220	0.9210	0.9380
Eff	ave	1.2996	−1.2999	0.9998	−0.4996	0.5002	−0.5000
	std	0.0116	0.0116	0.0117	0.0111	0.0068	0.0079
		0.0123	0.0124	0.0124	0.0120	0.0075	0.0081
	95%	0.9480	0.9550	0.9570	0.9450	0.9630	0.9520
Local	ave	1.2992	−1.3010	1.0007	−0.4993	0.5011	−0.5001
	std	0.0155	0.0210	0.0209	0.0140	0.0142	0.0147
dMAVE	ave	1.2405	−1.3422	1.0303	−0.4490	0.5114	−0.5134
	std	0.0229	0.0151	0.0133	0.0153	0.0081	0.0082
SIR	ave	0.3064	−1.6387	1.2390	0.2477	0.4697	−0.4743
	std	0.1248	0.3965	0.3149	0.1057	0.1135	0.1141
DR	ave	0.3424	0.8686	−0.6620	−0.6895	−0.1923	0.1912
	std	0.2550	1.2518	0.9653	0.6938	0.3360	0.3410