[R] bootstrapped cox regression (rms package)

[Frank Harrell]

Thanks Eric.  It would be good to show your entire script next time as stated
in the posting guidance.

Regarding matching with SPSS please describe the bootstrapping algorithm
used there.  In rms I do the unconditional bootstrap, i.e., I sample with
replacement from the rows of the raw data.  And also make sure that SPSS ran
a large number of bootstrap replications.

Frank


Eric Claus wrote
> Hi Frank,
> Below is the actual output from the anova(out) command.  I had copied in
> the p-values and from the previous output from anova(out) and the
> confidence intervals from print(quantile(out$boot.Coef[,i], c(.025,
> .975))) to illustrate that the confidence intervals were similar to SPSS
> while the p-values were not.
> 
> Actual output from anova.rms(out):
> 
>  Wald Statistics          Response: Surv(months, recidivate) 
> 
>  Factor   Chi-Square d.f. P     
> fac1  0.27       1    0.6055
> fac2  0.20       1    0.6514
> fac3  0.01       1    0.9338
> fac4  0.05       1    0.8311
> fac5  1.06       1    0.3036
> fac6  0.33       1    0.5647
> fac7  0.81       1    0.3670
> fac8  0.30       1    0.5832
>  TOTAL   1.48       8    0.9930
> 
> Regarding your second question, it looks like SPSS is using the original
> estimate of Cox beta coefficients in the test (i.e. a new point estimate
> is not generated for the statistical test)
> 
> Thanks again,
> Eric





-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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