IntSurvDiff: Weighted Integrated Survival function test

Description

Computes a two sample weighted integrated survival function log-rank statistic with events weighted according to one of the available weighting function choices

Usage

IntSurvDiff(formula =formula(data), data =parent.frame(), WtFun =c("FH", "SFH", "Ramp"),
              param = c(0, 0), sided = c(2, 1), subset, na.action, w = FALSE)

Arguments

formula

a formula of the form Surv(Time, Event) ~ arm where arm is a dichotomous variable with values 0 and 1.

data

a dataframe

WtFun

a selection from the available list: “FH” (Fleming-Harrington), “SFH” (stopped Fleming-Harrington) or “Ramp”. See param in the following line.

param

Weight function parameters. Length and interpretation depends upon the selected value of WtFun: If WtFun==“FH” then param is a length 2 vector specifying the power of the pooled (across arms) kaplan meier estimate and its complement. If WtFun==“SFH” then param is a length 3 vector with first two components as in the “FH” case, and third component the time (in the same units as the time to event) at which the “FH” weight function is capped off at its current value. If WtFun==SFH then param is of length 1 specifying the time (same units as time to event) at which events begin to get equal weight. The “Ramp” weight function is a linearly increasing deterministic weight function which is capped off at 1 at the user specified time.

sided

One or Two sided test? Set to 1 or 2

subset

Analysis can be applied to a subset of the dataframe based upon a logical expression in its variables

na.action

Method for handling NA values in the covariate, arm

currently no effect

Value

An object of class survtest containing components

sample size

wttyp

internal representation of the WtFun argument

par

internal representation of the param argument

time

unique times of events accross all arms

nrisk

number at risk accross all arms at each event time

nrisk1

Number at risk in the experimental arm at each event time

nevent

Number of events accross all arms at each event time

nevent1

Number of events in the experimental arm at each event time

Values of the weight function at each event time

pntimes

Number of event times

stat

The un-normalized weighted log-rank statistic, i.e. the summed weighted observed minus expected differences at each event time

var

Variance estimate for the above

pu0

person units of follow-up time in the control arm

pu1

person units of follow-up time in the intervention arm

events in the control arm

events in the intervention arm

sample size, same as pn

call

the call that created the object

References

Weiand S, Gail MH, James BR, James KL. (1989). A family of nonparametric statistics for comparing diagnostic makers with paired or unpaired data. Biometrika 76, 585-592.

Examples

Run this code

# NOT RUN {
  library(PwrGSD)
  data(lung)
  fit.isd<-IntSurvDiff(Surv(time,I(status==2))~I(sex==2), data=lung, WtFun="SFH", param=c(0,1,300))
# }