plotSurvivalPvaluesByCutoff {psichomics} | R Documentation |
Plot p-values of survival difference between groups based on multiple cutoffs
plotSurvivalPvaluesByCutoff( clinical, data, censoring, event, timeStart, timeStop = NULL, followup = "days_to_last_followup", significance = 0.05, cutoffs = seq(0, 0.99, 0.01) )
clinical |
Data frame: clinical data |
data |
Numeric: elements of interest to test against the cutoff |
censoring |
Character: censor using |
event |
Character: name of column containing time of the event of interest |
timeStart |
Character: name of column containing starting time of the interval or follow up time |
timeStop |
Character: name of column containing ending time of the interval (only relevant for interval censoring) |
followup |
Character: name of column containing follow up time |
significance |
Numeric: significance threshold |
cutoffs |
Numeric: cutoffs to test |
p-value plot
Other functions to analyse survival:
assignValuePerSubject()
,
getAttributesTime()
,
labelBasedOnCutoff()
,
optimalSurvivalCutoff()
,
plotSurvivalCurves()
,
processSurvTerms()
,
survdiffTerms()
,
survfit.survTerms()
,
testSurvival()
clinical <- read.table(text = "2549 NA ii female 840 NA i female NA 1204 iv male NA 383 iv female 1293 NA iii male") names(clinical) <- c("patient.days_to_last_followup", "patient.days_to_death", "patient.stage_event.pathologic_stage", "patient.gender") clinical <- do.call(rbind, rep(list(clinical), 5)) psi <- data.frame(t(c(rep(0.1, 9), rep(0.2, 13), rep(0.3, 3)))) colnames(psi) <- paste0("sample", seq(psi)) # Match between subjects and samples match <- paste0("subject", seq(psi)) names(match) <- colnames(psi) rownames(clinical) <- match eventData <- assignValuePerSubject(psi[1, ], match) event <- "days_to_death" timeStart <- "days_to_death" plotSurvivalPvaluesByCutoff(clinical, eventData, censoring="right", event=event, timeStart=timeStart)