Peter O'Brien's test for association of a single variable with survival
Usage
survobrien(formula, data)
Arguments
formula
|
a valid formula for a cox model, without time dependent covariates.
|
data
|
a data frame.
|
Value
a new data frame. The original time and status variables are removed,
and have been replaced with start
, stop
, and event
.
If a predictor variable is a factor, it is retained as is.
Other predictor variables have been replaced with time-dependent logit
scores.
Because of the time dependent variables, the new data frame will have many
more rows that the original data, approximately #rows * #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.See Also
survdiff
Examples
data(ovarian)
xx <- survobrien(Surv(time, status) ~ age + factor(rx) + ecog.ps,
data=ovarian)
coxph(Surv(start, stop, event) ~ age, data=xx)
coxph(Surv(start, stop, event) ~ age + rx + ecog.ps, data=xx)