Description
Peter O'Brien's test for association of a single variable with survival
This test is proposed in Biometrics, June 1978.Usage
survobrien(formula, data, subset, na.action, transform)
Arguments
formula
a valid formula for a cox model.
data
a data.frame in which to interpret the variables named in
the formula
, or in the subset
and the weights
argument.
subset
expression indicating which subset of the rows of data should be used in
the fit. 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
.
transform
the transformation function to be applied at each
time point. The default is O'Brien's suggestion logit(tr) where
tr = (rank(x)- 1/2)/ length(x) is the rank shifted to the range
0-1 and logit(x) = log(x/(1-x)) is the logit transform.
Value
a new data frame. The response variables will be column names
returned by the Surv
function, i.e., "time" and "status" for
simple survival data, or "start", "stop", "status" for counting
process data. Each individual event time is identified by the
value of the variable .strata.
. Other variables retain
their original names. If a
predictor variable is a factor or is protected with I()
, it is
retained as is. Other predictor variables have been replaced with
time-dependent logit scores. The new data frame will have many
more rows that the original data, approximately the original number
of rows * number of deaths/2.Method
A time-dependent cox model can now be fit to the new data.
The univariate statistic, as originally proposed, is equivalent to
single variable score tests from the time-dependent model.
This equivalence is the rationale for using the time dependent model as a
multivariate extension of the original paper. In O'Brien's method, the x variables are re-ranked at each death time. A
simpler method, proposed by Prentice, ranks the data only once at the
start. The results are usually similar.References
O'Brien, Peter, "A Nonparametric Test for Association with Censored Data",
Biometrics 34: 243-250, 1978.Examples
Run this codexx <- survobrien(Surv(futime, fustat) ~ age + factor(rx) + I(ecog.ps),
data=ovarian)
coxph(Surv(time, status) ~ age + strata(.strata.), data=xx)
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