Good morning,
I have a data design which includes 3 factors of interest/*experimental
manipulations* (using Barr et. al?s (2013) terminology); namely *Listgp*
(listener group: T[monolinguals], TA [bilinguals] and TQ [Turkish speakers
who know Arabic through reading Quran]), *length* (long and short vowels)
and *context (emphatics, pharyngeals, plain and q)*.
*Listgp* is a *between-listener* (subject) and *within-stimulus* (item)
variable [(1|listener), (1+Listgp|stimulus)] while both *length* and
*context* are *within-listener* and *between-stimulus* variables
[(1+length|listener), (1|stimulus) and (1+context|listener), (1|stimulus)].
My question is, how can I code this in the following maximal model lacking
the random effects (for the time being?
maxmodal<- glmer(match ~ Listgp + length + context + gender + age + freq.,
data = msba, family = "binomial", control = glmerControl(optimizer =
"bobyqa"), nAGQ =1)
Here is more information on the variables involved.
*DV/Y (response):* match
*Random effects:* listener and stimulus
*Fixed effects/predictors:* a) *By-listener predictors*+ b) *by-stimulus
predictors: *
*a) By-listener predictors:* (*3*)
*1. Factors: (2)*
-*Listgp* (listener group): effect of interest (T: monolingual Turkish
speakers, TA: bilingual Turkish speakers and TQ: Turkish speakers who know
Arabic through reading Quran).)
-*gender* (female and male)
*2. Continuous predictors (1)*
-*age *(age of listeners at the time of experiment)
*b) By-stimulus predictors: (3)*
*1. Factors: (2)_*
-* context *(stimulus context: emphatic, pharyngeal, plain and q)
-*length *(stimulus length: long and short)
*2. Continuous predictors: (1)*
-*freq*. (stimulus frequency as per arabiCorpus)
Number of obs: 1224, groups: listener, 51; stimulus, 24
Appreciating your kind input.
--
Shad
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