Hi Frank,
Good to know. Thanks again for your help!
Kim
On Wed, Nov 10, 2010 at 8:53 AM, Frank Harrell wrote:
>
> Unfortunately, bootcov is not meant to operate on fit objects produced by
> fit.mult.impute. bootcov "gets there too late" in the process and does not
> know how to penalize for i
Hello,
I am using R.12.2.0. I am trying to generate bootstrap confidence intervals
using bootcov from the rms package. I am able to impute the missing data
using aregImpute and to perform a linear regression on the imputed datasets
using fit.mult.impute, but I am unable to use bootcov to generat
Thank you! That has fixed the problem.
Kim
On Tue, Nov 2, 2010 at 7:42 AM, Frank Harrell wrote:
>
> I tried your code with the rms package (replacement for the Design package;
> see http://biostat.mc.vanderbilt.edu/Rrms) and it worked fine.
>
> Note that multiple imputation needs the outcome var
Hello,
I would like to use the aregImpute and fit.mult.impute to impute missing
values for my dataset and then conduct logistic regression analyses on the
data, taking into account that we imputed values. I have no problems
imputing the values using aregImpute, but I am getting an error at the
fi
Hello,
I am using the val.prob function in the Design package. I understand how
the Brier quadratic error score is calculated, but I do not know how the
Brier score computed on the calibrated rather than raw predicted
probabilities (B cal) is calculated. My question is: how are the calibrated
pr
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