Measuring and correcting bias in indirect estimates of under-5 mortality in populations affected by HIV/AIDS: a simulation study

Table 4 Prediction errors from models to correct bias in indirect estimates of U5M

Method	Sample	Root mean square error	Root median square error	Mean relative error	Median relative error
Full Linear Model	in-sample	0.002973	0.001111	2.340	0.390
Full Linear Model	out-of-sample	0.014922	0.004183	1.970	1.082
Forward Sel. BIC	in-sample	0.002988	0.001143	2.325	0.392
Forward Sel. BIC	out-of-sample	0.014914	0.004152	1.966	1.087
Forward Sel. AIC	in-sample	0.002975	0.001132	2.324	0.389
Forward Sel. AIC	out-of-sample	0.014925	0.004184	1.968	1.084
Backward Sel. BIC	in-sample	0.002974	0.001110	2.331	0.389
Backward Sel. BIC	out-of-sample	0.014923	0.004182	1.966	1.082
Backward Sel. AIC	in-sample	0.002974	0.001110	2.331	0.389
Backward Sel. AIC	out-of-sample	0.014923	0.004182	1.966	1.082
glmnet, alpha = 0	in-sample	0.003241	0.001135	2.571	0.406
glmnet, alpha = 0	out-of-sample	0.003256	0.001150	1.100	0.382
glmnet, alpha = 0.5	in-sample	0.002985	0.001139	2.265	0.389
glmnet, alpha = 0.5	out-of-sample	0.002968	0.001177	0.965	0.376
glmnet, alpha = 1	in-sample	0.002985	0.001137	2.314	0.391
glmnet, alpha = 1	out-of-sample	0.002967	0.001175	0.960	0.374
PCR, ncomp = 20	in-sample	0.003989	0.002094	4.295	0.647
PCR, ncomp = 20	out-of-sample	0.014700	0.005351	3.004	1.455
PCR, ncomp = 30	in-sample	0.003122	0.001430	1.789	0.407
PCR, ncomp = 30	out-of-sample	0.014953	0.004504	1.868	1.101
PCR, ncomp = 35	in-sample	0.002994	0.001163	1.722	0.369
PCR, ncomp = 35	out-of-sample	0.014925	0.004281	1.836	1.087
PLS, ncomp = 16	in-sample	0.002988	0.001154	1.844	0.382
PLS, ncomp = 16	out-of-sample	0.014925	0.004264	1.872	1.087
PLS, ncomp = 32	in-sample	0.002973	0.001110	2.356	0.389
PLS, ncomp = 32	out-of-sample	0.014922	0.004183	1.976	1.082

Note: BIC Bayesian Information Criterion, AIC Akaike Information Criterion, glmnet generalized linear model via penalized maximum likelihood, where alpha is the elastic-net penalty term, PCR principle components regression; PLS partial least squares, ncomp number of components

ISSN: 1471-2458