Computes a two sample weighted integrated survival function log-rank statistic with events weighted according to one of the available weighting function choices
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formula |
a formula of the form |
data |
a dataframe |
WtFun |
a selection from the available list: “FH” (Fleming-Harrington),
“SFH” (stopped Fleming-Harrington) or “Ramp”. See |
param |
Weight function parameters. Length and interpretation depends upon
the selected value of |
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 |
w |
currently no effect |
An object of class survtest
containing components
pn |
sample size |
wttyp |
internal representation of the |
par |
internal representation of the |
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 |
call |
the call that created the object |
Grant Izmirlian <izmirlian@nih.gov
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.
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Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
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