[R-sig-ME] FW: Variogram / confint prediction in LMM / time prediction some questions from Switerland area

[mudryjm]

Sent: Sunday, August 1, 2021 5:32 PM
To: mudryjm <mudryjm using bluewin.ch>
Subject: Re: Variogram / confint prediction in LMM / time prediction some questions from Switerland area

 

I regret that I am not able to answer your questions at this time.  It has been a couple of decades since I worked on the nlme package and I have not kept up with the literature.

 

I suggest that you send your questions to the R-SIG-Mixed-Models using R-project.org <mailto:R-SIG-Mixed-Models using R-project.org>  mailing list.  Some information about the list is available at https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

 

On Sun, Aug 1, 2021 at 9:25 AM mudryjm <mudryjm using bluewin.ch <mailto:mudryjm using bluewin.ch> > wrote:

Dear Mr Bates and Pinhero

Tks for your incredible packages in R I did my master in statistics (attached). I’m a big fan!

However I’m puzzled with several theoretical questions on some topic where I’m struggling; instead of luring for stat input I asks directly WIZARDS!:


Variograms (Cressie):P 52 PDF

I have done several variograms on my model residuals expecting flat line along (sill flat).However some patient are at sill some on the correlation path-slope.

Q:How to interpret? (Two class of patient with biophysical discerpancies?

Q:The smoother fitted in graph is the theoretical one (Theoretical variogram based on exp?spherical?)?? Or is it a simple smoother.

Q: Is it possible with variogram (within (patient and sampling error) cor + between from LMM variance) to forecast the best time for re-measure?
I.e in cholesterol study some authors demonstrated when intra- variability exceed between variability? So measuring on too short intervals has no value.But I don’t know how to proceed

Or do you had a good reference.?

 

Fiiting confindance bands on XB+ZU:

 

Q.I try to get con band for predictings patients trajectories. As they is no close form (at least very complex) is the better way to bootstrap some model and fit a bootstrap confint on the 1000 Fitted values? Or do you have a smplier function?

 

Q:If I should predict when time  will be  reached for a patient his Upper reference limit how do I have to proceed? (back reversing formula?)
Page 54 :patients prediction

Tks for your help in an old retrained statistician

 

NB Your contribution to staworld is fabulous and inspired me in my daily work since  a year!

:)

 

Veuillez recevoir mes sincères salutations , 

Sincerely,

 

Mudry Jean-Marie

8 ch du Châno

1802 CORSEAUX 

Switzerland

 

+41.79.708.87.15

+41.21.921.10.18.

 

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