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)

Value

An object of class survtest containing components

pn: 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
wt: 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
n0: events in the control arm
n1: events in the intervention arm
n: sample size, same as pn
call: the call that created the object

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
w: currently no effect

Author

Grant Izmirlian <izmirlian@nih.gov

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

  library(PwrGSD)
  data(lung)
  fit.isd<-IntSurvDiff(Surv(time,I(status==2))~I(sex==2), data=lung, WtFun="SFH", param=c(0,1,300))

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