[R] Data manipulation for random intercept GLMM

[Ben Bolker]

Giovanni Petris <GPetris <at> uark.edu> writes:

> > ## Example: Ratings of prime minister (Agresti, Table 12.1, p.494)
> > rating <- matrix(c(794, 86, 150, 570), 2, 2)
> > dimnames(rating) <- list(First = c("approve", "disapprove"),
> +                          Second = c("approve", "disapprove"))
> > rating
>             Second
> First        approve disapprove
>   approve        794        150
>   disapprove      86        570
>
[snip]
> 
> > approval <- factor(c("Approve", "Disapprove"),
> +                    levels = c("Disapprove", "Approve"))
> > survey <- factor(c("First", "Second"))
> > tmp <- data.frame(approval = unlist(expand.grid(approval, approval)),
> +                   survey = rep(survey, each = 4))
> > rat.df <- cbind(tmp[rep(1:8, rep(rating, 2)), ],
> +                 id = factor(rep(1:sum(rating), 2)))
> > row.names(rat.df) <- NULL
> 
> That does the job, since now I can call lmer:
> 
> > m1 <- lmer(approval ~ survey + (1 | id), family = binomial, data = rat.df,
> +            method = "Laplace")
> 
[snip]

> 
> Consider also that the next simplest example is the following, in
> which there are three items on a questionnaire and gender is included
> in the model:
> 
> > ### Example: Support for legalizing abortion (Agresti, Table 10.13, p.441)
> > legalize <- matrix(c(342, 440, 26, 25, 6, 14, 21, 18, 11, 14,
> +                      32, 47, 19, 22, 356, 457), nr = 2)
> > dimnames(legalize) <- list(Gender = c("Male", "Female"),
> +                            Three = c(111, 112, 211, 212, 121,
> +                            122, 221, 222))
> > legalize
>         Three
> Gender   111 112 211 212 121 122 221 222
>   Male   342  26   6  21  11  32  19 356
>   Female 440  25  14  18  14  47  22 457
> 
> (Here '111' means (Yes, Yes, Yes) on the three items, etc.)
> 
> How can I tranform elegantly this table into a dataframe that I can
> feed to lmer?
> 

  I would like to know the answers to this as well.  I thought
I was going to be able to get away with as.data.frame.table()
[which is handy and underappreciated], but it doesn't expand
counts.
   I hope you get an elegant solution: in the meantime, I guess
my advice is to try to write a reasonably general (if not necessarily
absolutely elegant) function that you can supply your students with.
If they have an expand.table() function, they won't care how complex
it is internally ...

  Ben Bolker