BMC Medical Research Methodology

Table 5 Estimated RMSE of estimators for the cut-off θ by varying distributional assumptions on the continuous risk indicator X for unbalanced sample sizes (60/20), (150/50) and (300,100) and Youden Index J = 0.8

From: oA novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology

		J = 0.8
		60/20		150/50		300/100
		Bias	RMSE	Bias	RMSE	Bias	RMSE
Normal, equal variances		θ = 7.141
	N	0.009	0.072	0.000	0.045	0.001	0.030
	TN	-0.034	0.093	-0.043	0.069	-0.043	0.057
	EMP	0.159	0.218	0.183	0.218	0.196	0.214
	KM	0.007	0.097	-0.004	0.065	-0.001	0.048
	DS	0.006	0.139	0.005	0.105	0.008	0.086
Normal^ (-1/3)		θ = 3.525
	N	0.406	0.480	0.443	0.478	0.465	0.489
	TN	-0.220	0.326	-0.252	0.289	-0.263	0.280
	EMP	0.425	0.637	0.480	0.595	0.484	0.551
	KM	0.299	0.424	0.197	0.267	0.156	0.200
	DS	0.014	0.375	0.026	0.287	0.011	0.225
Mix1		θ = 11.373
	N	0.298	0.352	0.302	0.325	0.307	0.318
	TN	0.008	0.183	0.014	0.117	0.015	0.082
	EMP	-0.094	0.346	-0.040	0.246	-0.032	0.190
	KM	0.154	0.284	0.108	0.183	0.084	0.135
	DS	-0.063	0.310	-0.013	0.232	-0.011	0.185
Mix2		θ = 11.305
	N	0.150	0.225	0.173	0.203	0.169	0.185
	TN	-0.087	0.164	-0.077	0.116	-0.081	0.104
	EMP	-0.074	0.295	-0.028	0.214	-0.022	0.170
	KM	0.014	0.180	0.017	0.118	0.005	0.088
	DS	-0.052	0.269	-0.008	0.202	-0.003	0.167
Mix3		θ = 13.837
	N	0.124	0.268	0.124	0.196	0.124	0.166
	TN	-0.099	0.263	-0.102	0.185	-0.103	0.152
	EMP	-0.096	0.407	-0.038	0.283	-0.020	0.221
	KM	0.037	0.306	0.023	0.183	0.018	0.126
	DS	-0.066	0.376	-0.009	0.269	-0.002	0.217
Mix4		θ = 13.887
	N	0.159	0.303	0.152	0.223	0.156	0.193
	TN	-0.055	0.267	-0.070	0.177	-0.067	0.135
	EMP	-0.068	0.458	-0.040	0.302	-0.008	0.242
	KM	-0.002	0.335	-0.026	0.208	-0.020	0.143
	DS	-0.030	0.419	-0.021	0.292	-0.003	0.237

DS = Dempfle and Stute estimator; EMP = empirical conditional distribution function method; J = Youden Index;
KM = Kernel method; N = Normal method; TN = transformed normal method

Back to article page

ISSN: 1471-2288

Contact us

General enquiries: journalsubmissions@springernature.com