valorate.plot.kaplan: PLOT KAPLAN-MEIER CURVES
In valorate: Velocity and Accuracy of the LOg-RAnk TEst

Description Usage Arguments Details Value Author(s) References See Also Examples

Plots the Kaplan-Meier Curves from two groups.

1
2
3

valorate.plot.kaplan(vro, clusters, p=valorate.survdiff(vro, clusters), 
  main, short.names=TRUE, draw.all=FALSE, mark="|", mark.cex=0.75, 
  margins=TRUE, col=2:3, col.all="skyblue")

`vro`	the valorate object.
`clusters`	a numerical or logical vector representing the two survival groups encoded in 1/TRUE for those 'mutated' (in the group of interest) or 1/FALSE for those who not. Basically this value is the 'x' vector in the VALORATE re-formulation. See references.
`p`	the estimated p-value of the log-rank test. The default is valorate.survdiff(vro, clusters).
`main`	typical plot parameter. The default is an expression depending on the parameters.
`short.names`	if TRUE (default) use 'LR' instead or 'Log-Rank' and 'HR' instead or 'Hazard-Ratio' in legends.
`draw.all`	if TRUE, the plot includes also the survival curve of all subjects before stratification.
`mark`	character to mark censoring. The default is "\|".
`mark.cex`	the character expansion. The default is 0.75
`margins`	if TRUE (default) set the margins properly.
`col`	specifies the colors for survival curves. The default is 2:3 (red for cluster=0, green for cluster=1).
`col.all`	specifies the color when draw.all is TRUE. The default is "skyblue".

Plots the estimated Kaplan-Meier survival curves from data.

Nothing.

Victor Trevino vtrevino@itesm.mx

Trevino et al. 2016 http://bioinformatica.mty.itesm.mx/valorateR

new.valorate. valorate.survdiff.

## Create a random population of 100 subjects 
## having 20 events
subjects <- numeric(100)
subjects[sample(100,20)] <- 1
vo <- new.valorate(rank=subjects, sampling.size=100000, verbose=TRUE)

groups <- numeric(100)
groups[sample(100,20)] <- 1  # 20 to likely see some difference
pvr <- valorate.survdiff(vo, groups) 
print(pvr)

## Not run: valorate.plot.kaplan(vo, groups, main="Two Curves")

## Not run: valorate.plot.kaplan(vo, groups, draw.all=TRUE, 
    main="Three Curves (Including All Data)")
## End(Not run)