survdiffTerms {psichomics}R Documentation

Test Survival Curve Differences

Description

Tests if there is a difference between two or more survival curves using the G-rho family of tests, or for a single curve against a known alternative.

Usage

survdiffTerms(survTerms, ...)

Arguments

survTerms

survTerms object: survival terms obtained after running processSurvTerms (see examples)

...

Arguments passed on to survival::survdiff

subset

expression indicating which subset of the rows of data should be used in the fit. This can be a logical vector (which is replicated to have length equal to the number of observations), a numeric vector indicating which observation numbers are to be included (or excluded if negative), or a character vector of row names to be included. All observations are included by default.

na.action

a missing-data filter function. This is applied to the model.frame after any subset argument has been used. Default is options()$na.action.

rho

a scalar parameter that controls the type of test.

timefix

process times through the aeqSurv function to eliminate potential roundoff issues.

Value

a list with components:

n

the number of subjects in each group.

obs

the weighted observed number of events in each group. If there are strata, this will be a matrix with one column per stratum.

exp

the weighted expected number of events in each group. If there are strata, this will be a matrix with one column per stratum.

chisq

the chisquare statistic for a test of equality.

var

the variance matrix of the test.

strata

optionally, the number of subjects contained in each stratum.

METHOD

This function implements the G-rho family of Harrington and Fleming (1982), with weights on each death of S(t)^rho, where S is the Kaplan-Meier estimate of survival. With rho = 0 this is the log-rank or Mantel-Haenszel test, and with rho = 1 it is equivalent to the Peto & Peto modification of the Gehan-Wilcoxon test.

If the right hand side of the formula consists only of an offset term, then a one sample test is done. To cause missing values in the predictors to be treated as a separate group, rather than being omitted, use the factor function with its exclude argument.

References

Harrington, D. P. and Fleming, T. R. (1982). A class of rank test procedures for censored survival data. Biometrika 69, 553-566.

Examples

clinical <- read.table(text = "2549   NA ii  female
                                840   NA i   female
                                 NA 1204 iv    male
                                 NA  383 iv  female
                               1293   NA iii   male
                                 NA 1355 ii    male")
names(clinical) <- c("patient.days_to_last_followup", 
                     "patient.days_to_death",
                     "patient.stage_event.pathologic_stage",
                     "patient.gender")
timeStart  <- "days_to_death"
event      <- "days_to_death"
formulaStr <- "patient.stage_event.pathologic_stage + patient.gender"
survTerms  <- processSurvTerms(clinical, censoring="right", event, timeStart,
                               formulaStr=formulaStr)
survdiffTerms(survTerms)

[Package psichomics version 1.10.2 Index]