Print method for gsym.point objects

Description

Default print method for objects fitted with gsym.point() function. A short summary is printed with: the call to the gsym.point() function for each categorical covariate level (if the categorical.cov argument of the gsym.point() function is not NULL).

Usage

## S3 method for class 'gsym.point'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

Arguments

Author(s)

M<c3><b3>nica L<c3><b3>pez-Rat<c3><b3>n, Carmen Cadarso-Su<c3><a1>rez, Elisa M. Molanes-L<c3><b3>pez and Emilio Let<c3><b3>n

See Also

gsym.point, summary.gsym.point

Examples

library(GsymPoint)
data(elastase)

###########################################################
# Empirical Likelihood 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) 

gsym.point.GPQ.elastase

print(gsym.point.GPQ.elastase)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(GsymPoint)
Loading required package: truncnorm
Loading required package: Rsolnp
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GsymPoint/print.gsym.point.Rd_%03d_medium.png", width=480, height=480)
> ### Name: print.gsym.point
> ### Title: Print method for gsym.point objects
> ### Aliases: print.gsym.point
> 
> ### ** Examples
> 
> library(GsymPoint)
> data(elastase)
> 
> ###########################################################
> # Empirical Likelihood 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) 
According to the Shapiro-Wilk normality test, the original marker 
can not be considered normally distributed in both groups.
After transforming the marker using the Box-Cox transformation 
estimate the Shapiro-Wilk normality test indicates that the 
transformed marker can not be considered normally distributed 
in both groups. 
Therefore, the results obtained with the GPQ method may not be 
reliable. You must use the EL method instead.

Box-Cox lambda estimate = 0.1136 

Shapiro-Wilk test p-values
                           Group 0 Group 1
Original marker             0.0746  0.0091
Box-Cox transformed marker  0.0000  0.0793
> 
> gsym.point.GPQ.elastase

Call:
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)

Optimal cutoffs:
     GPQ
 34.7163

Area under the ROC curve (AUC):  0.744
> 
> print(gsym.point.GPQ.elastase)

Call:
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)

Optimal cutoffs:
     GPQ
 34.7163

Area under the ROC curve (AUC):  0.744
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>