D. Bautista et al., Validation of logistic regression models in small samples: Application to calvarial lesions diagnosis, J CLIN EPID, 52(3), 1999, pp. 237-241
Citations number
24
Categorie Soggetti
Envirnomentale Medicine & Public Health","Medical Research General Topics
We have used the leave one out (LOO) method and the area under the receiver
operating characteristic (ROC) curve to validate logistic models with a sa
mple of 167 patients with calvarial lesions. Seven logistic regression mode
ls were developed from 12 clinical and radiological variables to predict th
e most common diagnoses separately. The LOO method was used to test the val
idity of the equations. The discriminant power of every model was assessed
by means of the area under the ROC curve (A(z)). The model with the greates
t discrimination ability for the whole data set was the osteoma equation (A
(z) = 0.951). The discriminatory ability of the statistical models decrease
d significantly with the LOO procedure, having the malignancy model the hig
hest value (A(z) = 0.931). The LOO method can obtain a high benefit from sm
all samples in order to validate prediction rules. In studies with small sa
mples, resampling techniques such as the LOO should be routinely used in pr
edictive modeling. This method may improve the forecast of infrequent disea
ses, such as calvarial lesions. J CLIN EPIDEMIOL 52;3:237-241, 1999. (C) 19
99 Elsevier Science Inc.