[R-sig-ME] using a continuous-valued variable as fixed effect
abfine at gmail.com
Mon Sep 21 20:58:55 CEST 2015
Yes, MEMs can accommodate continuous-valued predictors, just like in
classical regression (GLMs). It's also possible and very common to model
interactions between continuous and categorical predictors. Their
interpretation is also essentially the same as in GLMs. I'd recommend
Gelman and Hill (2007), Chapters 11-13 for a nice introduction.
On Mon, Sep 21, 2015 at 7:55 AM, Francesco Sigona <
francesco.sigona at unisalento.it> wrote:
> Hi all,
> I'm a newbie with linear mixed model.
> I just would like to know if it is possible to use one or more variables
> assuming values in a continuous range (e.g. a frequency values in Hz) as
> fixed effects, in a linear mixed model, possibly together with (or without)
> categorical (binary) effects, using lmer4 package.
> In case: how to do it and how to read the results, in terms of statistical
> Can anyone explain if in this case mixed models are actually different
> from a simple (multiple) linear regression?
> Why should mixed models be preferred to linear regression in this case?
> Thank you in advance.
> *Francesco SIGONA*
> Electronics engineer
> Piazza Filippo Muratore
> 73100 - Lecce - Italy <
> tel.: +39 0832 335006
> fax.: +39 0832 335007
> *Center for Interdisciplinary Research on Language (CRIL) <
> http://www.cril.unisalento.it> &
> Cognitive Neuroscience of Language and Speech Sciences Lab (CNLSS) *
> *Dipartimento di Studi umanistici
> Università del Salento *
> *Laboratorio Diffuso di Ricerca Interdisciplinare Applicata alla Medicina
> (DReAM) *
> R-sig-mixed-models at r-project.org mailing list
Ph. (336) 302-3251
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