Hi All, I dont think it is contradictory to use the sample-based densities for integration and then use the classical EBE for reporting individual values. When integrating you want to see the entire individual density so you can give correct weight to large areas of low probability. But when you are reporting individual values you dont really care about large areas of low probability, you only want the “most likely” parameters for an individual, this is classical EBEs or the (approximated) mode of the distribution.
The mean of this density is numerically useful but doesnt have a easy to understand interpretation (for me at least). warm regards, Douglas Eleveld ________________________________________ From: [email protected] [[email protected]] on behalf of De Ridder, Filip [JRDBE] [[email protected]] Sent: Wednesday, August 08, 2012 10:06 PM To: Bauer, Robert; [email protected] Subject: [NMusers] RE: NM7.2 SAEM with LIKE Hi Bob, Apparently, Monolix offers two options side by side: mean or mode. However, is there not another difference here: root.phi gives the conditional mean of the sampling-based posterior density, whereas using FNLETA gives you the "classical" EBE, i.e. not sampling based? It seems a bit contradictory that you would use the sampled-based densities to integrate out the ETA's in SAEM to obtain the pop pars, and then not use the sampled-based densities to get the ETA's? Any thoughts are welcome. Kind regards, Filip -----Oorspronkelijk bericht----- Van: Bauer, Robert [mailto:[email protected]] Verzonden: wo 8/08/2012 0:30 Aan: De Ridder, Filip [JRDBE]; [email protected] Onderwerp: RE: NM7.2 SAEM with LIKE Filip: In your case it may be that conditional means are more appropriate than conditional modes, but I would not necessarily conclude that in general. I do not know what Monolix reports regarding individual parameters. Robert J. Bauer, Ph.D. Vice President, Pharmacometrics, R&D ICON Development Solutions 7740 Milestone Parkway Suite 150 Hanover, MD 21076 Tel: (215) 616-6428 Mob: (925) 286-0769 Email: [email protected] Web: www.iconplc.com<http://www.iconplc.com/> ________________________________ From: De Ridder, Filip [JRDBE] [mailto:[email protected]] Sent: Tuesday, August 07, 2012 3:08 PM To: Bauer, Robert; [email protected] Subject: RE: NM7.2 SAEM with LIKE Hi Bob, Thanks for the clarification. Would you agree that the conditional means are more trustworthy, in case there is a relevant difference? In my specific dataset, there are 5 subjects for whom the conditional means yield a much better individual fit, than the "post-hoc" eta's. I believe that in Monolix, the individual parameter estimates are the conditional means, no? In my example Kind regards, Filip -----Oorspronkelijk bericht----- Van: Bauer, Robert [mailto:[email protected]] Verzonden: di 7/08/2012 18:28 Aan: De Ridder, Filip [JRDBE]; [email protected] Onderwerp: RE: NM7.2 SAEM with LIKE Filip: The $TABLE results are obtained from a "post-hoc" assessment at the best fit eta values (modal, EBE), regardless of the method used. To evaluate $TABLE parameters at the conditional mean positions, you may select FNLETA=0. Robert J. Bauer, Ph.D. Vice President, Pharmacometrics, R&D ICON Development Solutions 7740 Milestone Parkway Suite 150 Hanover, MD 21076 Tel: (215) 616-6428 Mob: (925) 286-0769 Email: [email protected] Web: www.iconplc.com<http://www.iconplc.com/> ________________________________ From: [email protected] [mailto:[email protected]] On Behalf Of De Ridder, Filip [JRDBE] Sent: Tuesday, August 07, 2012 10:18 AM To: [email protected] Subject: [NMusers] NM7.2 SAEM with LIKE Dear All, With NM7.2/SAEM, the root.phi output file contains the conditional means (and variances) of the individual phi's (mu(i)+eta(i)) - which is great! I found that the these values can be different from what you get from a $TABLE in more classical way: $PRED MU_1=THETA(1) K=MU_1+ETA(1) ... $TABLE K ... For a some subjects, these are very different, and the ones coming from the $TABLE are clearly less optimal, yielding a bad individual fit, as judged from IPRE calculated in $PRED. I guess one part of the solution is using CPRED and CPREDI - but unfortunately I cannot use these as I (have to) use LIKELIHOOD in $EST (M3 method for BLQ-data). Kind regards, Filip De Ridder Janssen R&D, Beerse, Belgium. ICON plc made the following annotations. ------------------------------------------------------------------------------ This e-mail transmission may contain confidential or legally privileged information that is intended only for the individual or entity named in the e-mail address. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or reliance upon the contents of this e-mail is strictly prohibited. If you have received this e-mail transmission in error, please reply to the sender, so that ICON plc can arrange for proper delivery, and then please delete the message. 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