survobrien: O'Brien's Test for Association of a Single Variable with Survival

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)

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 or is protected with I(), 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.

Examples

Run this code

data(ovarian)
xx <- survobrien(Surv(futime, fustat) ~ age + factor(rx) + I(ecog.ps),
			       data=ovarian)
coxph(Surv(start, stop, event) ~ age, data=xx)
coxph(Surv(start, stop, event) ~ age + rx + ecog.ps, data=xx)

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