Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

Table 1 Sample demographics: The two groups in the criterion were "MCI" - Mild Cognitive impaired patients; and "Dementia" patients.

	MCI	Dementia	p-value
Group size (%)	275(69%)	125 (31%)	<0.001^‡
Age (M ± SD)	67.8 ± 8.8	71.6 ± 8.4	<0.001^†
Sex (♀/♂)	165/110	78/47	0.649^‡
Schooling years (M ± SD)	8.1 ± 4.7	8.64 ± 4.9	0.469^†
Time between assessments (year)(M ± SD)	2.3 ± 1.6	2.2 ± 1.4	0.517^†

The class to predict was "Dementia". P-values for group comparison were obtained from Student's-t test (†) or χ² test (‡).

ISSN: 1756-0500