Re: [NMusers] inclusion of covariates with $PRIOR

From: Jakob Ribbing <jakob.ribbing_at_pharmetheus.com>
Date: Thu, 16 May 2019 11:45:18 +0200

Dear Anna,

The times I have used SCM in combination with a frequentist prior, it =
has been only to test if a new population is different (i.e. the data =
used to generate the prior were all of a different population, e.g. =
healthy volunteers and other indications than the currently-investigated =
population.
Or something similar where the covariate value is a nominal level which =
was not present in the data used to generate the prior).
To use SCM in combination with NWPRI in that situation is =
straightforward.

With regards to your first question. If you use a prior only to support =
the estimation of this specific covariate coefficient (no prior on other =
parameters), then you do not need to center around the same covariate =
value.
The point estimate for the covariate coefficient will be the same, =
regardless of how you center these covariate models (but standard =
errors, correlation between estimates and the covariance matrix as a =
whole will be different depending on how you center).
However, with prior across all model parameters, it would be important =
to center across the same covariate value, since the population typical =
value is with regards to this (e.g. the population typical clearance for =
a subject with 70 kg body weight).
Maybe this is what Gisleskog et al. were referring to?

With regards to model selection with a prior on all available parameters =
this is not as straightforward.
If your prior is a full model (including all covariates that you want to =
test in SCM), then in principle using prior on all fixed effects would =
be possible.
But due to correlation between the estimates in your prior you could end =
up leaving a covariate out of the model, in a way that would not have =
happened in a combined analysis.

An alternative may be to have separate priors for each model you test, =
but I do not think there is any automated software to support that =
procedure.

If you have access to the data used to generate the prior, it may be =
easier to combine all data, rather than using a frequentist prior.
I suspect this is not possible in your case, since you ask these =
questions?

Best regards

Jakob





Jakob Ribbing, Ph.D.

Senior Consultant, Pharmetheus AB



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Received on Thu May 16 2019 - 05:45:18 EDT

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