Re: Stepwise covariate modeling
Hi,
I am not 100% certain that a decrease in the IIV terms associated with the
covariate-parameter relationships is a criteria used in the automated selection
process implemented by the PsN scm command (at least I could not find any
reference in the documentation). You may want to implement a more manual
approach to the problem where you define your own set of criteria for covariate
selection that you would apply at each step.
PS: our KIWI platform can help you with the automated creation of univariate
runs at each step and summarization of results while keeping you in control of
the covariate selection criteria...
---
Sébastien Bihorel
Director, Pharmacometrics and KIWI™ applications
Cognigen Corporation, a SimulationsPlus company
Buffalo Office: +1 716 633 3463 ext. 323 |
https://www.simulations-plus.com/cognigen/
Quoted reply history
________________________________
From: [email protected] <[email protected]> on behalf of
Singla, Sumeet K <[email protected]>
Sent: Tuesday, October 29, 2019 10:00
To: [email protected] <[email protected]>
Subject: [NMusers] Stepwise covariate modeling
Hi!
I am performing stepwise covariate modeling using PsN feature in Pirana. I am
getting some covariates which are statistically reducing OFV significantly,
however, when I include those covariates in the PK model, the results I am
getting are exactly similar to what I am getting in my base model, i.e. there
is no difference in individual predictions or pop predictions or any other
diagnostic plots. So, does that mean I should move forward WITHOUT including
those covariates as they don’t seem to be explaining inter-individual
variability despite scm telling me that they are statistically significant?
Regards,
Sumeet K. Singla
Ph.D. Candidate
Division of Pharmaceutics and Translational Therapeutics
College of Pharmacy | University of Iowa
Iowa City, Iowa
[email protected]<mailto:[email protected]>
518.577.5881