Re: [External] Re: [NMusers] RE: Stepwise covariate modeling

[Muhammad Usman]

I suspect you are using same file name at the bottom of model for base
model as well as final model after inclusion of covariates. Please check,
if so then use different file name for final model. I hope this can work.

Regards

Usman

On Tue, Oct 29, 2019, 8:57 PM Singla, Sumeet K 
wrote:

> Thank you everyone for taking time out of your busy schedule to reply to
> my question. I think all points were excellent. Gives me more to think
> about how to proceed from here and make more informed decision about my
> model.
>
> Regards,
> Sumeet
>
> -Original Message-
> From: Leonid Gibiansky 
> Sent: Tuesday, October 29, 2019 10:36 AM
> To: Luann Phillips ; Singla, Sumeet K <
> sumeet-sin...@uiowa.edu>; nmusers@globomaxnm.com
> Subject: [External] Re: [NMusers] RE: Stepwise covariate modeling
>
> I think we are making it more difficult than needed, especially for the
> people who just started using the NLME. It does not hurt to include
> statistically significant covariate in the model even if the actual effect
> is small and does no manifest itself on the standard diagnostic plots.
>
> It make sense to check whether there is an error in the model code.
> Plots of random effects versus covariates of interest should help to see
> whether covariate model changed the individual random effects. If not (that
> is, random effects of the model with and without covariate effect are
> numerically identical) then the coding is wrong and should be checked.
>
> Thanks
> Leonid
>
>
>
> On 10/29/2019 11:00 AM, Luann Phillips wrote:
> > Hi,
> >
> > If _all_ of the individual predictions are the same for the model with
> > the covariate and without the covariate, then it sounds like the
> > original model is at a local minimum instead of a global minimum.
> >
> > Best regards,
> >
> > Luann
> >
> > *From:* owner-nmus...@globomaxnm.com 
> > *On Behalf Of *Singla, Sumeet K
> > *Sent:* Tuesday, October 29, 2019 10:00 AM
> > *To:* nmusers@globomaxnm.com
> > *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*
> >
> > *sumeet-sin...@uiowa.edu <mailto:sumeet-sin...@uiowa.edu>*
> >
> > *518.577.5881*
> >
>
>

RE: [External] Re: [NMusers] RE: Stepwise covariate modeling

[Singla, Sumeet K]

Thank you everyone for taking time out of your busy schedule to reply to my 
question. I think all points were excellent. Gives me more to think about how 
to proceed from here and make more informed decision about my model.

Regards,
Sumeet

-Original Message-
From: Leonid Gibiansky  
Sent: Tuesday, October 29, 2019 10:36 AM
To: Luann Phillips ; Singla, Sumeet K 
; nmusers@globomaxnm.com
Subject: [External] Re: [NMusers] RE: Stepwise covariate modeling

I think we are making it more difficult than needed, especially for the people 
who just started using the NLME. It does not hurt to include statistically 
significant covariate in the model even if the actual effect is small and does 
no manifest itself on the standard diagnostic plots.

It make sense to check whether there is an error in the model code. 
Plots of random effects versus covariates of interest should help to see 
whether covariate model changed the individual random effects. If not (that is, 
random effects of the model with and without covariate effect are numerically 
identical) then the coding is wrong and should be checked.

Thanks
Leonid



On 10/29/2019 11:00 AM, Luann Phillips wrote:
> Hi,
> 
> If _all_ of the individual predictions are the same for the model with 
> the covariate and without the covariate, then it sounds like the 
> original model is at a local minimum instead of a global minimum.
> 
> Best regards,
> 
> Luann
> 
> *From:* owner-nmus...@globomaxnm.com  
> *On Behalf Of *Singla, Sumeet K
> *Sent:* Tuesday, October 29, 2019 10:00 AM
> *To:* nmusers@globomaxnm.com
> *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*
> 
> *sumeet-sin...@uiowa.edu <mailto:sumeet-sin...@uiowa.edu>*
> 
> *518.577.5881*
> 

Re: [NMusers] RE: Stepwise covariate modeling

[Leonid Gibiansky]

I think we are making it more difficult than needed, especially for the 
people who just started using the NLME. It does not hurt to include 
statistically significant covariate in the model even if the actual 
effect is small and does no manifest itself on the standard diagnostic 
plots.


It make sense to check whether there is an error in the model code. 
Plots of random effects versus covariates of interest should help to see 
whether covariate model changed the individual random effects. If not 
(that is, random effects of the model with and without covariate effect 
are numerically identical) then the coding is wrong and should be checked.


Thanks
Leonid



On 10/29/2019 11:00 AM, Luann Phillips wrote:

Hi,

If _all_ of the individual predictions are the same for the model with 
the covariate and without the covariate, then it sounds like the 
original model is at a local minimum instead of a global minimum.


Best regards,

Luann

*From:* owner-nmus...@globomaxnm.com  *On 
Behalf Of *Singla, Sumeet K

*Sent:* Tuesday, October 29, 2019 10:00 AM
*To:* nmusers@globomaxnm.com
*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*

*sumeet-sin...@uiowa.edu *

*518.577.5881*

[NMusers] RE: Stepwise covariate modeling

[Luann Phillips]

Hi,

If all of the individual predictions are the same for the model with the 
covariate and without the covariate, then it sounds like the original model is 
at a local minimum instead of a global minimum.

Best regards,
Luann

From: owner-nmus...@globomaxnm.com  On Behalf Of 
Singla, Sumeet K
Sent: Tuesday, October 29, 2019 10:00 AM
To: nmusers@globomaxnm.com
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
sumeet-sin...@uiowa.edu
518.577.5881

[NMusers] Re: Stepwise covariate modeling

[Sebastien Bihorel]

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 | 
Website

From: owner-nmus...@globomaxnm.com  on behalf of 
Singla, Sumeet K 
Sent: Tuesday, October 29, 2019 10:00
To: nmusers@globomaxnm.com 
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

sumeet-sin...@uiowa.edu

518.577.5881