[R-sig-ME] Reference ?

Shane Frank @h@ne@|r@nk @end|ng |rom u@n@no
Sun Dec 5 03:26:24 CET 2021

Hi SV,

I think there is doubt whether a ‘small’ sample size adequately represents your population of interest. You can argue from a study design perspective that you avoided bias with a random sample, but the game of (low) numbers during sampling could create a bias due to randomness as well. ‘Trusting’ your estimates and the uncertainty around them goes beyond the fitting process. I apologize if this is obvious to you. But, I think this push-pull idea might help explain why it is difficult to give you some coup de grace reference to ‘solve’ your problem. I think your rationale and argumentation will be more helpful than a reference anyway. Perhaps that was what FB was insinuating. You could try sensitivity analysis to help bolster your confidence in the results if that was your goal.


From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> on behalf of Fernando Pedro Bruna Quintas <f.bruna using udc.es>
Sent: Saturday, December 4, 2021 12:55:18 PM
To: R-sig-mixed-models <r-sig-mixed-models using r-project.org>; varin sacha <varinsacha using yahoo.fr>
Subject: Re: [R-sig-ME] Reference ?

Dear SV,

I can feel that you have a very promising research career just in front of your eyes.


De: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> en nombre de varin sacha via R-sig-mixed-models <r-sig-mixed-models using r-project.org>
Enviado: s�bado, 4 de diciembre de 2021 20:47
Para: R-sig-mixed-models <r-sig-mixed-models using r-project.org>
Asunto: [R-sig-ME] Reference ?

Dear Mixed modelers experts,

I am looking for a reference to justify my sentence here below.
Many thanks for your help.

"The mixed model seemed well specified � it converged and had no singular problem, no overfitting problem. So, even if the sample size is quite small, the estimates are stable and can be trusted".

Best Regards,

R-sig-mixed-models using r-project.org mailing list

        [[alternative HTML version deleted]]

	[[alternative HTML version deleted]]

More information about the R-sig-mixed-models mailing list