summary.optimal.cutpoints: Summary method for optimal.cutpoints objects

In OptimalCutpoints: Computing Optimal Cutpoints in Diagnostic Tests

Description

Produces a summary of a optimal.cutpoints object. The following are printed: the call to the optimal.cutpoints() function; the optimal cutpoint(s) obtained with the method(s) selected; its/their accuracy measures and the area under ROC curve (AUC) estimates at each categorical covariate level (if the categorical.cov argument in the optimal.cutpoints() function is not NULL). If optimal.cutpoints() was called with the ci.fit = TRUE argument, confidence intervals for accuracy measures at the optimal cutpoint are also printed.

Usage

## S3 method for class 'optimal.cutpoints'
summary(object, ...)

Arguments

object	an object of class optimal.cutpoints as produced by optimal.cutpoints()
...	further arguments passed to or from other methods. None are used in this method.

Details

The summary.optimal.cutpoints function produces a list of summary information for a fitted optimal.cutpoints object. The result depends on the three arguments, namely, methods, categorical.cov and ci.fit of the optimal.cutpoints() function used in the optimal cutpoints computing process.

Value

Returns an object of class "summary.optimal.cutpoints" with the same components as the optimal.cutpoints function (see optimal.cutpoints) plus:

p.table

a list with all the numerical information to be shown on the screen.

Author(s)

Monica Lopez-Raton and Maria Xose Rodriguez-Alvarez

See Also

optimal.cutpoints

Examples

library(OptimalCutpoints)
data(elas)
###########################################################
# Youden Index Method ("Youden"): Covariate gender
###########################################################
optimal.cutpoint.Youden<-optimal.cutpoints(X = "elas", status = "status", tag.healthy = 0, 
methods = "Youden", data = elas, pop.prev = NULL, categorical.cov = "gender", 
control = control.cutpoints(), ci.fit = TRUE, conf.level = 0.95, trace = FALSE)

summary(optimal.cutpoint.Youden) 

Example output

Warning: Sensitivity CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Specificity CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Positive Predictive Value CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Negative Predictive Value CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Sensitivity CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Specificity CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Positive Predictive Value CI: "Exact" method may not be valid for some values (see Help Manual).

Warning: Negative Predictive Value CI: "Exact" method may not be valid for some values (see Help Manual).


Call:
optimal.cutpoints.default(X = "elas", status = "status", tag.healthy = 0, 
    methods = "Youden", data = elas, categorical.cov = "gender", 
    pop.prev = NULL, control = control.cutpoints(), ci.fit = TRUE, 
    conf.level = 0.95, trace = FALSE)

*************************************************
Female
*************************************************

Area under the ROC curve (AUC):  0.818 (0.684, 0.952) 

CRITERION: Youden
Number of optimal cutoffs: 1

                    Estimate 95% CI lower limit 95% CI upper limit
cutoff            46.0000000                  -                  -
Se                 0.6666667          0.3838037          0.8817589
Sp                 0.8181818          0.5971542          0.9481327
PPV                0.7142857          0.4516107          0.9031160
NPV                0.7826087          0.5285570          0.9359958
DLR.Positive       3.6666667          1.4096667          9.5373214
DLR.Negative       0.4074074          0.1939348          0.8558589
FP                 4.0000000                  -                  -
FN                 5.0000000                  -                  -
Optimal criterion  0.4848485                  -                  -


*************************************************
Male
*************************************************

Area under the ROC curve (AUC):  0.722 (0.612, 0.831) 

CRITERION: Youden
Number of optimal cutoffs: 1

                    Estimate 95% CI lower limit 95% CI upper limit
cutoff            38.0000000                  -                  -
Se                 0.6543210          0.5404147          0.7565737
Sp                 0.7391304          0.5159480          0.8977139
PPV                0.8983051          0.7686835          0.9355009
NPV                0.3777778          0.2738718          0.6528595
DLR.Positive       2.5082305          1.2382379          5.0807845
DLR.Negative       0.4676834          0.3180320          0.6877538
FP                 6.0000000                  -                  -
FN                28.0000000                  -                  -
Optimal criterion  0.3934514                  -                  -

OptimalCutpoints documentation built on Oct. 7, 2021, 5:09 p.m.