[R] using betareg: problems with anova and predict

[Achim Zeileis]

On Mon, 17 Apr 2006, Paul Johnson wrote:

> Dear R-helpers:
>
> We have had fun using betareg to fit models with proportions as
> dependent variables.
>
> However, in the analysis of these models we found some wrinkles and
> don't know where is the best place to start looking for a fix.
>
> The problems we see (so far) are that
>
> 1. predict ignores newdata

The reason for this is that predict.betareg() does not take a newdate
argument, you need to use the terms argument instead.

> 2. anova does not work

...because there is no anova() method for betareg objects.

I think it is owrth addressing both issues in betareg, I'll write to you
and Alexandre (the package maintainer) off-list.
Z

> Here is the small working example:
>
> ----------------------------
> x <- c(1, 3, 1, 4, 5, 3, 5, 2, 5, 2)
> y <- c(.3, .4, .4, .5, , .7, .4, .3, .4, .3, .5)
> x2 <- c( 4, 2, 1, 5, 1, 2, 4, 2, 1, 3)
> library(betareg)
> mybreg <- betareg(y~x)
> summary(mybreg)
>
> predict(mybreg, newdata=data.frame(x=c(2,2)))
>
> mybreg2 <- betareg(y~x+x2)
> summary(mybreg)
> anova(mybreg, mybreg2)
>
> -------------------------------
> Example output:
>
> > predict(mybreg, newdata=data.frame(x=c(2,2)))
>  [1] 0.3903155 0.4207632 0.3903155 0.4362319 0.4518258 0.4207632 0.4518258
>  [8] 0.4054484 0.4518258 0.4054484
> ...
> > anova(mybreg, mybreg2)
> Error in as.double.default(lapply(objects, df.residual)) :
> 	(list) object cannot be coerced to 'double'
>
> I have been digging in this a little bit and notice betareg does not
> return the log likelihood at the maximum likelihood estimates, but I
> am able to hack the file /usr/lib/R/library/betareg/R/betareg and save
> the "value" of the optim function and print that out, so at least I
> can do a likelihood-ratio test by hand in place of the anova.  But I'm
> stumped on why the predict ignores newdata.
>
> I'm using R-2.1.1 on Fedora Core Linux 5 with the betareg package from CRAN.
>
> In case you are interested in betareg, we have found this article to
> be extremely readable and helpful: FERRARI, S.L.P., CRIBARI-NETO, F.
> (2004). Beta regression for  modeling rates and proportions. Journal
> of Applied Statistics, v. 31, n. 7, p. 799-815.
>
>
> --
> Paul E. Johnson
> Professor, Political Science
> 1541 Lilac Lane, Room 504
> University of Kansas
>
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