Hi all
I am embarking on a project to derive a clinical prediction rule (using
logistic regression) and it has been suggested that I should use a
bootstrapping technique to study the internal validity of the final prediction
model in order to derive bias-corrected coefficients/odds ratios.
Perusing the manuals I came across the bstrap command which seems like a good
place to start. I have been able to use a simple logistic regression in the
bstrap command to calculate bias-corrected coefficients/odds ratios. However,
I have seen articles that have suggested that they have used a stepwise
command within the bootstrapping routine, ie replicating the exact same
procedure that I will used to arrive at the final prediction model in each of
the 1000 samples. I am unable to get bstrap to implement the sw command.
I know that I can simply derive 1000 samples and apply the sw procedure to
each sample. However, I am unsure as to how to assimilate the data from these
1000 samples as not only will the magnitude of the coefficients vary in each
sample (simple part!) but the actual variables chosen by each sw procedure may
be different in each sample.
Any help with programming in Stata or detailed examples in the literature
(many just glibly state that this process was carried out � very helpful!)
would be appreciated
Best wishes
Elaine Thomas
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