Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.

Skip to main content

Table 4 Characteristics of the multiple logisitic regression models in VALID sampler

From: Development and validation of a dietary screener for carbohydrate intake in endurance athletes

model

Sensitivity

Specificity

False positives

False negatives

PPV

NPV

c statistic

5 variablesa

52.6

82.2

12.0

15.4

58.8

78.2

0.71

10 variables

75.4

86.4

9.1

8.0

72.9

87.9

0.90

15 variables

89.5

87.3

8.6

3.4

77.3

94.5

0.94

  1. PPV positive predictive value, NPV negative predictive value
  2. a % (all such values)