[R-sig-ME] Measurement error for mixed models

[Doran, Harold]

This error-in-variables approach is not available in lme. I do have an R-based implementation of this for models with random intercepts. You can find this implementation at:

https://shiny.airast.org/METRICS/

And a complete tutorial is under the Help tab.

-----Original Message-----
From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> On Behalf Of Krzysztof Bartoszek via R-sig-mixed-models
Sent: Wednesday, September 11, 2019 10:02 AM
To: r-sig-mixed-models using r-project.org
Subject: [R-sig-ME] Measurement error for mixed models

Dear all,
As far as I managed to see the weights parameter in nlme::lme(), mgcv::gamm(), gamm4::gamm4(), can be used to pass some specific residual variance structure based on nlme's varFunc class. I was wondering if the following variance structure is possible to be obtained from the already implemented instances in varClasses, or I will need to code it myself.

I want the variance of the response for observation i to be of the form v_i^2 = s^2 + s_i^2, where s^2 is a common for all observations unknown variability and s_i^2 is known, individual specific measurement error variance (can be 0).

Thank you
Best wishes
Krzysztof Bartoszek

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