Table 1.

Summary of simulation results under MAR. Values shown are averages over repeat sampling, with numerical Monte Carlo standard errors in parentheses. GP, LM, LM–, DPM, DPM– represent the proposed semiparametric model, the linear regression model with covariates, the linear regression model without covariates, the Dirichlet process mixture model with covariates and the Dirichlet process mixture model without covariates, respectively. CI width and coverage are based on 95% credible intervals.

Model	Bias	CI width	CI coverage	MSE
	Scenario 1
GP	−0.013(0.004)	0.294(0.002)	0.909(0.012)	0.014(0.000)
LM	−0.005(0.004)	0.379(0.001)	0.969(0.007)	0.017(0.000)
LM–	0.004(0.004)	0.385(0.002)	0.969(0.007)	0.018(0.001)
DPM	−0.013(0.004)	0.355(0.002)	0.954(0.009)	0.018(0.001)
DPM–	−0.009(0.004)	0.343(0.001)	0.947(0.009)	0.016(0.001)
	Scenario 2
GP	0.037(0.010)	0.967(0.005)	0.943(0.010)	0.122(0.004)
LM	0.247(0.010)	1.021(0.004)	0.819(0.017)	0.189(0.006)
LM–	0.330(0.010)	1.094(0.005)	0.783(0.018)	0.243(0.007)
DPM	0.183(0.011)	1.188(0.006)	0.924(0.012)	0.192(0.005)
DPM–	0.302(0.011)	1.054(0.006)	0.781(0.019)	0.228(0.008)
	Scenario 3
GP	−0.005(0.007)	0.666(0.002)	0.958(0.009)	0.057(0.002)
LM	0.008(0.007)	0.705(0.002)	0.968(0.008)	0.061(0.002)
LM–	0.026(0.007)	0.707(0.002)	0.964(0.008)	0.061(0.002)
DPM	−0.008(0.008)	0.778(0.002)	0.984(0.006)	0.070(0.002)
DPM–	−0.001(0.007)	0.669(0.002)	0.953(0.010)	0.058(0.002)