Random slopes for 2 variables and random intercept for 1 variable

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

	[[alternative HTML version deleted]]