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Re: [NMusers] ETAs & SIGMA in external validation

From: Tingjie Guo <iam_at_tingjie.name>
Date: Fri, 6 Apr 2018 21:40:19 +0200

Small correction in question 2: *SIGMA* (instead of OMEGA) value influences
individual ETAs...


_at_Leonid, _at_Jakob, Thank you both for your input.

_at_Jakob, You are right, I'm interested in individual ETAs. The idea is to
evaluate the predictive ability of the model in particular subjects
(external data) in order to guide clinical care for these subjects. Does
this purpose alter your opinion on SIGMA choice?


Yours sincerely,
Tingjie Guo


On Fri, Apr 6, 2018 at 7:51 PM, Leonid Gibiansky <lgibiansky_at_quantpharm.com>
wrote:

> It would be better to use
>
> $EST METHOD=1 INTERACTION MAXEVAL=0
>
> (at least if the original model was fit with INTERACTION option and
> residual error model is not additive).
>
> One option is to use Para = THETA * EXP(ETA)
> You would be changing the model, but the model is not too good any way if
> you need to restrict Para > 0 artificially.
>
> SIGMA should be taken from the model.
>
> Leonid
>
>
>
> On 4/6/2018 12:32 PM, Tingjie Guo wrote:
>
>> Dear NMusers,
>>
>> I have two questions regarding the statistical model when performing
>> external validation. I have a dataset and would like to validate a
>> published model with POSTHOC method i.e. $EST METHOD=0 POSTHOC MAXEVAL=0.
>>
>> 1. The model added etas in proportional way, i.e. Para = THETA * (1+ETA)
>> and this made the posthoc estimation fail due to the negative individual
>> parameter estimate in some subjects. I constrained it to be positive by
>> adding ABS function i.e. Para = THETA * ABS(1+ETA), and the estimation can
>> be successfully running. I was wondering if there is better workaround?
>>
>> 2. OMEGA value influences individual ETAs in POSTHOC estimation. Should
>> we assign $SIGMA with model value or lab (where external data was
>> determined) assay error value? If we use model value, it's understandable
>> that $SIGMA contains unexplained variability and thus it is a part of the
>> model. However, I may also understand it as that model value contains the
>> unexplained variability for original data (in which the model was created)
>> but not for external data. I'm a little confused about it. Can someone help
>> me out?
>>
>> I would appreciate any response! Many thanks in advance!
>>
>> Your sincerely,
>>
>> Tingjie Guo
>>
>>


Received on Fri Apr 06 2018 - 15:40:19 EDT

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