summary.gsym.point: Summary method for gsym.point objects

In GsymPoint: Estimation of the Generalized Symmetry Point, an Optimal Cutpoint in Continuous Diagnostic Tests

Summary method for gsym.point objects

Description

Produces a summary of a gsym.point object. The following is printed: the matched call to the gsym.point() main function; the area under the ROC curve (AUC) estimate; the Generalized Symmetry point obtained with the method(s) selected and the point estimates of the associated sensitivity and specificity indexes with their corresponding confidence intervals. All this information will be shown for each categorical covariate level (if the categorical.cov argument in the gsym.point() function is not NULL).

Usage

## S3 method for class 'gsym.point'
summary(object, ...)

Arguments

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

Details

The summary.gsym.point function produces a list of summary information for a fitted gsym.point object. The result depends on the two arguments, namely, methods, and categorical.cov of the gsym.point() function used in the Generalized Symmetry point computing process.

Value

Returns an object of class "summary.gsym.point" with the same components as the gsym.point function (see gsym.point)

Author(s)

Mónica López-Ratón, Carmen Cadarso-Suárez, Elisa M. Molanes-López and Emilio Letón

See Also

gsym.point

Examples

library(GsymPoint)

data(melanoma)

###########################################################
# Generalized Pivotal Quantity Method ("GPQ"): 
###########################################################

gsym.point.GPQ.melanoma<-gsym.point(methods = "GPQ", data = melanoma,
marker = "X", status = "group", tag.healthy = 0, categorical.cov = NULL, 
CFN = 1, CFP = 1, control = control.gsym.point(),confidence.level = 0.95, 
trace = FALSE, seed = FALSE, value.seed = 3, verbose = FALSE)

summary(gsym.point.GPQ.melanoma)


data(prostate)

###########################################################
# Generalized Pivotal Quantity Method ("GPQ"): 
###########################################################

gsym.point.GPQ.prostate <- gsym.point (methods = "GPQ", data = prostate,
marker = "marker", status = "status", tag.healthy = 0, categorical.cov = NULL, 
CFN = 1, CFP = 1, control = control.gsym.point(), confidence.level = 0.95, 
trace = FALSE, seed = FALSE, value.seed = 3, verbose = FALSE)

summary(gsym.point.GPQ.prostate)


data(elastase)

###########################################################
# Generalized Pivotal Quantity Method ("GPQ"): 
###########################################################

gsym.point.GPQ.elastase <- gsym.point(methods = "GPQ", data = elastase, 
marker = "elas", status = "status", tag.healthy = 0, categorical.cov = NULL, 
CFN = 1, CFP = 1, control = control.gsym.point(), confidence.level = 0.95, 
trace = FALSE, seed = FALSE, value.seed = 3, verbose = FALSE) 

summary(gsym.point.GPQ.elastase)

GsymPoint documentation built on Nov. 2, 2023, 5:59 p.m.