Re: OFV by endpoint of joint models?
Hi Matts,
The easiest way to assess is when one of two endpoints is modeled directly (TTE, logistic regression) as often is the case, than look at the Y value for those endpoints, as reported in the PRED variable. The sum of those values is the ofv, or proportional to it, for that particular endpoint - the other endpoint is than affected in the inverse way.
If you have multiple continuous endpoints it becomes more complicated. You could either look at the sum of absolute CWRES to get an idea, but not exact in terms of ofv comparison. Another approximate comparison would be to run the model without evaluation (e.g. MAXEVAL=0) with the original msfofile as $MSFI for the separate endpoints (by e.g. IGN(DVID.NE.x) where x is your endpoint). It is not exact, again, as it ignores the correlation between endpoints but should get you in the neighborhood. As an improvement to this method you could force evaluation at the original posthocs by reading them in in your datafile - this would still ignore correlation but the effect would be largely diminished because the posthocs are fixed to those estimated with correlation.
Hope this helps,
Jeroen
http://pd-value.com
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@PD_value
+31 6 23118438
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Quoted reply history
On 10-10-2022 16:03, Matts Kågedal wrote:
> Hi all,
>
> I have a question related to the objective function value when multiple endpoints are modelled jointly. Specifically I would like to know if a change in in OFV between models is driven primarily by one of the endpoints or if both contributes to the change, or maybe they are even driving the OFV in oposite directions.
>
> Is there a way to get some form of partial OFV by endpoint?
> Best regards,
> Matts