[R-sig-ME] Multilevel logistic regression guessing parameter

Paul Buerkner paul.buerkner at gmail.com
Fri May 12 09:36:41 CEST 2017

Hi Dominik,

in addition to what Jake said, you can do this with the brms package (using
Stan under the hood). After installing brms, you can learn how to fit such
models in the "brms_nonlinear" vignette: Type vignette("brms_nonlinear") in


2017-05-11 13:00 GMT+02:00 Dominik Ćepulić <dcepulic at gmail.com>:

> I  have a following situation:
> I want to predict variable B (which is dichotomous) from variable A
> (continous) controlling for random effects on the level of a) Subjects; b)
> Tasks.
> A -> B (1)
> The problem is that when I use model to predict the values of B from A,
> values below probability of 0.5 get predicted, and in my case that doesn´t
> make sense, because, if you guess at random, the probability of correct
> answer on B would be 0.5.
> I want to know how I can constrain the model (1) in lme4 so that it doesn´t
> predict values lower than 0.5 in variable B.
> Thank you,
> Dominik!
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