[R] Data manipulation for random intercept GLMM

[Greg Snow]

Is this what you are trying to do?

> tt <- matrix( 5:10, ncol=2 )
> df <- as.data.frame.table(tt)
> df2 <- df[ rep( 1:nrow(df), df$Freq ), ]

And is that elegant enough?

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
(801) 408-8111
 
 

> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Ben Bolker
> Sent: Friday, May 02, 2008 7:36 AM
> To: r-help at stat.math.ethz.ch
> Subject: Re: [R] Data manipulation for random intercept GLMM
> 
> 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
> 
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