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. 2020 Mar 10;80(5):932–954. doi: 10.1177/0013164420911136

Table 1.

Average Bias, RMSE, and Correlation Values for MAR.

Method Test length Missing proportion (%) Bias RMSE Correlation
FIML 20 30 0.000 0.339 .916
MICE-CART 20 30 0.000 0.366 .902
MICE-RFI2 20 30 0.000 0.367 .900
MICE-CART2 20 30 0.000 0.373 .897
MICE-RFI 20 30 0.000 0.373 .896
Zero replacement 20 30 0.000 0.443 .854
FIML 40 30 0.000 0.282 .951
MICE-CART 40 30 0.000 0.304 .942
MICE-RFI2 40 30 0.000 0.311 .940
MICE-CART2 40 30 0.000 0.314 .938
MICE-RFI 40 30 0.000 0.314 .938
Zero replacement 40 30 0.000 0.384 .908
FIML 60 30 0.000 0.250 .964
MICE-CART 60 30 0.000 0.268 .958
MICE-RFI2 60 30 0.000 0.278 .955
MICE-RFI 60 30 0.000 0.280 .954
MICE-CART2 60 30 0.000 0.283 .953
Zero replacement 60 30 0.000 0.348 .929
FIML 20 40 0.000 0.406 .877
MICE-CART2 20 40 0.000 0.437 .857
MICE-CART 20 40 0.000 0.443 .853
MICE-RFI2 20 40 0.000 0.445 .850
Zero replacement 20 40 0.000 0.465 .845
MICE-RFI 20 40 0.000 0.470 .830
FIML 40 40 0.000 0.348 .924
MICE-CART 40 40 0.000 0.373 .912
MICE-CART2 40 40 0.000 0.378 .910
MICE-RFI2 40 40 0.000 0.382 .908
MICE-RFI 40 40 0.000 0.401 .898
Zero replacement 40 40 0.000 0.422 .891
FIML 60 40 0.000 0.311 .943
MICE-CART 60 40 0.000 0.332 .935
MICE-CART2 60 40 0.000 0.341 .931
MICE-RFI2 60 40 0.000 0.344 .930
MICE-RFI 60 40 0.000 0.358 .924
Zero replacement 60 40 0.000 0.400 .907
Zero Replacement 20 70 0.000 0.585 .738
FIML 20 70 0.000 0.658 .642
MICE-CART2 20 70 0.000 0.681 .607
MICE-RFI2 20 70 0.000 0.691 .572
MICE-CART 20 70 0.000 0.705 .580
MICE-RFI 20 70 0.000 0.747 .469
Zero replacement 40 70 0.000 0.543 .812
FIML 40 70 0.000 0.579 .776
MICE-CART2 40 70 0.000 0.604 .749
MICE-CART 40 70 −0.004 0.622 .733
MICE-RFI2 40 70 −0.001 0.631 .726
MICE-RFI 40 70 −0.001 0.698 .640
Zero replacement 60 70 0.000 0.523 .838
FIML 60 70 0.000 0.539 .820
MICE-CART2 60 70 −0.001 0.559 .803
MICE-CART 60 70 −0.005 0.568 .796
MICE-RFI2 60 70 −0.001 0.585 .787
MICE-RFI 60 70 −0.001 0.660 .709

Note. RMSE = root mean square error; MAR = missing at random; FIML = full-information maximum likelihood; MICE-CART = multiple imputation with chain equations utilizing classification and regression trees; MICE-RFI = multiple imputation with chain equations utilizing random forest imputation.