## Loading required package: carData
##
## Attaching package: 'ROCit'
## The following object is masked from 'package:car':
##
## logit
psychological + health
##
## Method used: empirical
## Number of positive(s): 175
## Number of negative(s): 79
## Area under curve: 0.7957
##
## estimated AUC : 0.795732368896926
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.74151800916655 upper = 0.849946728627302
##
## estimated AUC : 0.509584086799277
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.432944993377431 upper = 0.586223180221122
## A prediction instance
## with 254 data points
## A performance instance
## 'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
## with 112 data points
behavioral +health
##
## Method used: empirical
## Number of positive(s): 175
## Number of negative(s): 79
## Area under curve: 0.8233
##
## estimated AUC : 0.823254972875226
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.773045232057407 upper = 0.873464713693045
##
## estimated AUC : 0.470596745027125
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.393353085504718 upper = 0.547840404549532
## A prediction instance
## with 254 data points
## A performance instance
## 'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
## with 218 data points
environmental
##
## Method used: empirical
## Number of positive(s): 175
## Number of negative(s): 79
## Area under curve: 0.8089
##
## estimated AUC : 0.808933092224231
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.756590939313594 upper = 0.861275245134869
##
## estimated AUC : 0.435660036166365
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.358371287740141 upper = 0.512948784592589
## A prediction instance
## with 254 data points
## A performance instance
## 'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
## with 171 data points
psychological
##
## Method used: empirical
## Number of positive(s): 175
## Number of negative(s): 79
## Area under curve: 0.7301
##
## estimated AUC : 0.730126582278481
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.667824487330821 upper = 0.792428677226142
##
## estimated AUC : 0.510452079566004
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.433833022653768 upper = 0.587071136478239
## A prediction instance
## with 254 data points
## A performance instance
## 'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
## with 112 data points
behavioral
##
## Method used: empirical
## Number of positive(s): 175
## Number of negative(s): 79
## Area under curve: 0.7276
##
## estimated AUC : 0.727631103074141
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.665059011323358 upper = 0.790203194824924
##
## estimated AUC : 0.569547920433996
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.494961602178446 upper = 0.644134238689547
## A prediction instance
## with 254 data points
## A performance instance
## 'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
## with 218 data points
environmental
##
## Method used: empirical
## Number of positive(s): 175
## Number of negative(s): 79
## Area under curve: 0.7626
##
## estimated AUC : 0.762640144665461
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.704102382896282 upper = 0.82117790643464
##
## estimated AUC : 0.44253164556962
## AUC estimation method : empirical
##
## CI of AUC
## confidence level = 95%
## lower = 0.365214194374795 upper = 0.519849096764446
## A prediction instance
## with 254 data points
## A performance instance
## 'False positive rate' vs. 'True positive rate' (alpha: 'Cutoff')
## with 171 data points
