cox.zph

0th

Percentile

Test the Proportional Hazards Assumption of a Cox Regression

Test the proportional hazards assumption for a Cox regression model fit (coxph).

Keywords
survival
Usage
cox.zph(fit, transform="km", global=T)
Arguments
fit
the result of fitting a Cox regression model, using the coxph function.
transform
a character string specifying how the survival times should be transformed before the test is performed. Possible values are "km", "rank", "identity" or a function of one argument.
global
should a global chi-square test be done, in addition to the per-variable tests.
x
if true, then the result will be a list containing the test table (a matrix), x and y. If false then only the test table is returned.
table
a matrix with one row for each variable, and optionally a last row for the global test. Columns of the matrix contain the correlation coefficient between transformed survival time and the scaled Schoenfeld residuals, a chi-square, and the two-sided p-valu
x
the transformed time axis.
y
the matrix of scaled Schoenfeld residuals. There will be one column per variable and one row per event. The row labels contain the original event times (for the identity transform, these will be the same as x).
call
the calling sequence for the routine.

The computations require the original x matrix of the Cox model fit. Thus it saves time if the x=T option is used in coxph. This function would usually be followed by both a pl

Note

The plot method requires the splines library

References

P. Grambsch and T. Therneau (1994), Proportional hazards tests and diagnostics based on weighted residuals. Biometrika, 81, 515-26.

See Also

coxph, Surv.

Aliases
  • cox.zph
  • [.cox.zph
  • print.cox.zph
Examples
data(ovarian)
fit <- coxph( Surv(futime, fustat) ~ age + rx, ovarian)
temp<- cox.zph(fit)
print(temp)                  #display the results
plot(temp)                   #plot curves
Documentation reproduced from package survival, version 2.9-6, License: GPL2

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