optimal cut off with Epi package

[Luigi]

Dear all,

I would like to calculate the optimal cut off (threshold) of a test using
the Epi package. Here I am presenting some data based on the output of two
tests. I am interested in identifying the optimal cut off an its 95% CI.

Running the ROC() function with the Epi package I obtain a nice picture that
returns what I interpret as the optimal cut off with lr.eta=0.431. would be
this the optimal cut off? Otherwise I can I calculate it? And its confidence
interval?

Thank you,

Luigi Marongiu, MSc

 

####################################

test1<-c(  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
0,     0,   0,   0,   0,   0,   0,   0,   1,   1,   1,   1,   1,   1,   1,
1,     1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,
1,     1,   1,   1,   1,   1,   1)

 

test2<-c(  0.65662706,     0.009706075,    0.003134876,    0.049831384,
1.089876198,    0.136582023,    0.165812622,    1.316512535,    0.725196908,
6.214688703,    48.26356415,    0.004775112,    0.035568226,    0.36934994,
0.452627677,    1.001904226,    0.116876181,    0.127614619,    1.345812733,
1.487365838,    4.321874201,    0.373389928,    0.002137676,    0.019958462,
43.51470584,    10.07600936,    8.668998078,    11.2505088,     45.53510205,
49.80855616,    1.375550815,    9.798996492,    9.494694175,    23.24171357,
0.779040988,    664.0886249,    15.05400384,    2.365265177,    0.076619211,
0.692909116,    8.497272898,    15.57700003,    20.83909961,    0.833613282,
2.84624862,     0.46118499,     7.330049094,    1.612815795,    3.695709614,
17.75107595)

 

### create data frame from matrix

     my.mat<-matrix(c(test1, test2), nrow=50, byrow=FALSE)

     dimnames(my.mat)<-list(c(1:50),c("class", "test"))

     my.data<-as.data.frame(my.mat)

     attach(my.data)

 

### LOAD PACKAGE

     library(Epi)

 

### ROC analysis

           ROC(form=my.data$class ~ my.data$test, plot="ROC", data=my.data,

main="ROC with Epi package", MI=TRUE, MX=TRUE, PV=TRUE)

 

### REPORT: lr.eta=0.491


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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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[Frank Harrell]

It is not appropriate to seek a cutoff for a test unless every patient is known to have exactly the same utility function, which is extremely rare.  There is nothing wrong with developing probability models and stopping at that point, deferring the decision to the possessor of the utility function.
Frank

Luigi wrote

Dear all,

I would like to calculate the optimal cut off (threshold) of a test using
the Epi package. Here I am presenting some data based on the output of two
tests. I am interested in identifying the optimal cut off an its 95% CI.

Running the ROC() function with the Epi package I obtain a nice picture that
returns what I interpret as the optimal cut off with lr.eta=0.431. would be
this the optimal cut off? Otherwise I can I calculate it? And its confidence
interval?

Thank you,

Luigi Marongiu, MSc

 

####################################

test1<-c(  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
0,     0,   0,   0,   0,   0,   0,   0,   1,   1,   1,   1,   1,   1,   1,
1,     1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,   1,
1,     1,   1,   1,   1,   1,   1)

 

test2<-c(  0.65662706,     0.009706075,    0.003134876,    0.049831384,
1.089876198,    0.136582023,    0.165812622,    1.316512535,    0.725196908,
6.214688703,    48.26356415,    0.004775112,    0.035568226,    0.36934994,
0.452627677,    1.001904226,    0.116876181,    0.127614619,    1.345812733,
1.487365838,    4.321874201,    0.373389928,    0.002137676,    0.019958462,
43.51470584,    10.07600936,    8.668998078,    11.2505088,     45.53510205,
49.80855616,    1.375550815,    9.798996492,    9.494694175,    23.24171357,
0.779040988,    664.0886249,    15.05400384,    2.365265177,    0.076619211,
0.692909116,    8.497272898,    15.57700003,    20.83909961,    0.833613282,
2.84624862,     0.46118499,     7.330049094,    1.612815795,    3.695709614,
17.75107595)

 

### create data frame from matrix

     my.mat<-matrix(c(test1, test2), nrow=50, byrow=FALSE)

     dimnames(my.mat)<-list(c(1:50),c("class", "test"))

     my.data<-as.data.frame(my.mat)

     attach(my.data)

 

### LOAD PACKAGE

     library(Epi)

 

### ROC analysis

           ROC(form=my.data$class ~ my.data$test, plot="ROC", data=my.data,

main="ROC with Epi package", MI=TRUE, MX=TRUE, PV=TRUE)

 

### REPORT: lr.eta=0.491


        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.