Table 9.

MSE Ratios, N =500, Simulation B

	Listwise		Log		CART		RF		MI
	30%	50%	30%	50%	30%	50%	30%	50%	30%	50%
${\overline{X}}_2$
Linear	1.359	3.478	.933	.832	1.038	.960	1.066	1.624	.877	.576
One split	3.044	3.713	1.341	.943	1.021	1.042	4.923	2.183	.664	.668
Two splits	.979	.931	.847	.986	.968	.996	1.424	2.738	.638	.585
Three splits	3.344	2.837	.811	.685	1.035	.945	1.160	1.237	.686	.543
${\overline{Y}}_2$
Linear	1.565	5.940	.884	.569	1.047	.766	1.057	1.257	.883	.385
One split	6.089	8.160	1.685	.829	.963	.885	4.340	1.909	.533	.489
Two splits	1.044	1.500	.610	.662	.873	.967	1.590	2.708	.524	.450
Three splits	6.295	8.569	.713	.629	1.035	.882	1.238	1.994	.629	.522
${\mathrm{\sigma }}_{X_2}^2$
Linear	.860	.694	.901	1.084	1.063	1.112	1.046	1.696	.810	.645
One split	.666	.887	1.357	1.101	1.044	1.039	3.392	1.607	.551	.760
Two splits	.933	.711	1.002	.999	1.186	1.070	1.682	1.963	.754	.519
Three splits	.704	.736	.805	.910	1.199	1.096	1.301	1.204	.628	.697
${\mathrm{\sigma }}_{Y_2}^2$
Linear	.981	1.069	.985	1.241	1.066	1.101	.961	1.410	.736	.748
One split	1.155	.984	3.386	1.400	.966	.911	1.357	1.171	.458	.575
Two splits	1.831	1.544	1.843	1.419	1.056	.918	1.482	1.029	.571	.449
Three splits	.978	.655	.820	.905	1.005	.997	1.048	1.212	.518	.469
${\mathrm{\sigma }}_{X_2,Y_2}$
Linear	.884	.921	.933	1.221	1.045	1.207	1.078	1.718	.747	.656
One split	.889	.892	2.484	1.223	1.031	.925	2.488	1.187	.489	.564
Two splits	1.534	1.372	1.496	1.263	1.082	.946	1.375	1.470	.638	.454
Three splits	.860	.782	.738	.929	1.046	1.070	1.015	1.236	.553	.523

Note. MSE ratios computed over MSE_Prune. MSE = mean squared error; Log = logistic regression; CART = classification and regression trees; RF = random forests; MI = multiple imputation.