[R-lang] Re: Comparing effect sizes in lmer

[lngmyers@ccu.edu.tw]

I raised this question a few years ago on this list - you can see the
discussion here:

http://www.mail-archive.com/r-lang@ling.ucsd.edu/msg00058.html

I think the "best" answer is here:

http://www.mail-archive.com/r-lang@ling.ucsd.edu/msg00057.html

James S. Adelman wrote:

[begin quote]

If I've understood your question correctly, you are asking about a linear
regression model with response, say z, and two predictors x and y:

K: z = a  +  mx  +  ny  +  error

and you wish to know whether H0: m=n.  If so, anova(lm(z~x+y),lm(z~I(x+y)))
should be valid under the usual conditions.

[end quote]

I've since incorporated this logic into the R code underlying my
Optimality Theory testing program MiniCorp, as explained here (see
(10)-(13)):

http://www.ccunix.ccu.edu.tw/~lngproc/MCInfo.htm#stats

MiniCorp uses Poisson regression to test if two OT constraints must be
ranked or not. So it uses R code like the following:

NoRanking = glm(Count ~ I(AgreeV + IdentV), family = poisson)
Ranking = glm(Count ~ AgreeV + IdentV, family = poisson)
anova(NoRanking, Ranking, test = "Chisq")

- jm

On Thu, Feb 3, 2011 8:15 am, Ariel M. Goldberg wrote:
> Dear R-lang,
>
>
> I am interested in comparing the effect sizes of two predictors, A and B.
> When I standardize them and enter them both into my lmer model, the
> coefficient of one is twice the size of the other (-9 vs -4.5).  Is there
> a principled way to determine if A has a "significantly" greater effect?
> I was thinking that one way might be to compare the increase in
> loglikelihood over a baseline model but I'm not sure how to do it.  I'm
> envisioning something along the lines of creating 3 models: baseline,
> which contains neither of the two predictors, and baseline+A and
> baseline+B (which contain the baseline model and A and B, respectively),
> and then comparing how much each of the latter two models increases the
> loglikelihood over the baseline model.
>
> Any thoughts would be much appreciated!
> AG
>
>