st: Degrees of freedom in STPM2

[Adam Olszewski <adam.olszewski@gmail.com>]

Dear listreaders,
I have been wondering about an issue regarding the (user written,
SSC-derived) STPM2 command.
I am fitting flexible parametric models in datasets (disease subtypes)
of different sizes. Some are smaller than the others (ranging from 200
to 2500 in size) and in some the number of events is as low as 25 (out
of ~200).
Does the "10:1" rule (10 events per degree of freedom) used in Cox
modelling apply equally to these models? Since I'm studying a number
(about 8) of  variables in larger datasets, should I remove some of
the variables in a smaller dataset to stick to the 10:1 rule? Do the
degrees of freedom related to the spline knots need to be counted?
All of this interestingly does not make significant difference in
terms of the parameters of interest, however I would like to avoid
disputes with potential reviewers regarding different models applied
to subtypes of the same disease. For clarity and logical consistency,
I could fit the same model in all datasets using all variables
expected to affect the outcome, but for the smaller datasets the 10:1
rule would be grossly violated.
I wonder if there is a definite guidance with regards to this. This
might be even more complex with competing risk models. Thanks for any
insight!
Best regards,
Adam Olszewski
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