I have been studying a linguistic construction (let’s call it
C) in a language
L1 trying to individuate several factors (
Fn) which can influence / trigger the presence of
L1. All factors are categorical variables with several levels.
I ran basic significance tests (Goodness of fit) which revealed a high level of significance for each factors involved.
That said, I would now like to measure the interaction of all factors / all levels. As for the method, I think that Poisson Regression is what I am looking for since “C” has no levels and can be represented in terms of frequencies. I thus tried Poisson regression in R but I have soon run into several problems.
I have two questions in particular:
The data frame I used looked like that (here you can find only a tiny part of it as an example):
Subj (Factor1) NP (F2) New (F3) EXP_CON (F4)
To get the frequencies of all variable combinations, I used the function
ftableand then I went on manually computing the frequencies. Needless to say, it was a painful procedure and it took a lot of time!
Does R provide an easier and quicker way to get the frequencies for all the interacting factors / levels (possibly eliminating automatically the interactions whose frequency is zero)? In other words, I would like to obtain something like that:
Sub (F1) NP (F2) EXP_CON (F3) New (F4) (Freq) 6
After that, I tried to run a Poisson regression model but the result was puzzling. Here is an example of what I got:
Syn_FunOther:Focus_CCIMP_CON:IS_CCGiven NA NA NA NA Syn_FunSub:Focus_CCIMP_CON:IS_CCGiven NA NA NA NA Syn_FunOther:Focus_CCNO_CON:IS_CCGiven NA NA NA NA Syn_FunSub:Focus_CCNO_CON:IS_CCGiven NA NA NA NA Syn_FunOther:Focus_CCNOV:IS_CCGiven NA NA NA NA
I do not really understand. Why are there so many