[R] Joint confidence interval for fractional polynomial terms

[Eleni Rapsomaniki]

Dear Professor Harrell,

Once again thank you for your helpful reply. I could use rcs instead, so I
look forward to your latest rms release (soon I hope?)
Initially I favoured fractional polynomials thinking that the model would
be easier to present, but now I see that with either method unless one
plots the fitted function results are just as hard to interpret. That's
why the simultaneous CI plot will be very useful.

Eleni

> On Jan 9, 2012, at 8:45 AM, "Eleni Rapsomaniki" <e.rapsomaniki at ucl.ac.uk>
> wrote:
>
>> Dear R users,
>>
>> The package 'mfp' that fits fractional polynomial terms to predictors.
>> Example:
>> data(GBSG)
>> f <- mfp(Surv(rfst, cens) ~ fp(age, df = 4, select = 0.05)
>>                 + fp(prm, df = 4, select = 0.05), family = cox, data =
>> GBSG)
>> print(f)
>>
>> To describe the association between the original predictor, eg. age and
>> risk for different values of age I can plot it the polynomials and
>> fitted
>> coefficients as:
>>
>> plot(0.407*I((age/100)^-2) + -4.96*I((age/100)^-0.5) ~ age, GBSG)
>>
>> But I can't work out how to get a 95% confidence interval for this
>> curve... Any suggestions? I could bootstrap it, but is there a
>> mathematical solution?
>>
>> Many thanks
>> Eleni Rapsomaniki
>> Medical Statistician
>> UCL, London
>>
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>