[R-sig-ME] Graphing interaction terms in LME4, glmer
Ista Zahn
istazahn at gmail.com
Tue Jan 29 03:11:31 CET 2013
Hi Shane,
I think there may be some version issues here: on my system my example
worked fine.
I have
R version 2.15.2 (2012-10-26)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=C LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] effects_2.2-3 colorspace_1.2-0 nnet_7.3-5 MASS_7.3-23
[5] lme4_0.999999-0 Matrix_1.0-10 lattice_0.20-13
loaded via a namespace (and not attached):
[1] compiler_2.15.2 nlme_3.1-107 stats4_2.15.2 tools_2.15.2
Best,
Ista
On Mon, Jan 28, 2013 at 7:29 PM, Shane Gleason <sgleason at siu.edu> wrote:
> Hello everyone,
>
> Thank you kindly to everyone who replied. Ista's comment was the one that
> had exactly what I needed- though it did take some tinkering. For the
> benefit of the next person who comes along, I'm adding the changes I needed
> to make to Ista's code:
>
> Running the code Ista initially provided, the following error in bold comes
> up
>
>
>> data(cake, package="lme4")
>> cake$a2 <- ifelse(cake$angle < mean(cake$angle, na.rm=TRUE), 0, 1)
>>
>> fm1 <- lmer(a2 ~ recipe * temp + (1|recipe:replicate),
> + data = cake,
> + family = "binomial",
> + REML = FALSE)
>>
>> library(effects)
>> plot(effect("recipe:temp", fm1), grid=TRUE)
> Error in plot(effect("recipe:temp", fm1), grid = TRUE) :
> error in evaluating the argument 'x' in selecting a method for function
> 'plot': Error: $ operator not defined for this S4 class
>
> The solution to this is to follow on to the next line in the example in the
> effects display from John Fox's JSS paper http://www.jstatsoft.org/v08/i15:
>
> detach(package:lme4) # if previously attached
> library(nlme)
> data(cake, package="lme4")
>
> cake$rep <- with(cake, paste( as.character(recipe), as.character(replicate),
> sep=""))
> fm2 <- lme(angle ~ recipe * temperature, data=cake,
> random = ~ 1 | rep, method="ML")
> plot(effect("recipe", "temperature", fm2), grid=TRUE)
>
> However, this produces a heck of a lot of panels, which are kind of
> difficult to interpret.... so we force everything onto one graph- which is
> accomplished by adding the following line (also from John Fox's working
> paper (pg 14): (note, I haven't updated this to reflect the cake example
>
>> plot(effect("recipeism*extraversion", cowles.mod,
> +
> xlevels=list(neuroticism=0:24, extraversion=seq(0, 24, 6))),
> +
> multiline=TRUE, ylab="Probability(Volunteer)")
>
> You all have been a great help. I hope this summary e-mail helps others in
> the future.
>
> Shane
>
>
>
>
> On 01/28/2013 05:13 PM, Ista Zahn wrote:
>
> Hi Shane,
>
> Take a look at the effects package, I believe it has what you are
> looking for. Here is a modified example from ?effect
>
> library(lme4)
>
> data(cake, package="lme4")
> cake$a2 <- ifelse(cake$angle < mean(cake$angle, na.rm=TRUE), 0, 1)
>
> fm1 <- lmer(a2 ~ recipe * temp + (1|recipe:replicate),
> data = cake,
> family = "binomial",
> REML = FALSE)
>
> library(effects)
> plot(effect("recipe:temp", fm1), grid=TRUE)
>
>
> HTH,
> Ista
>
> On Mon, Jan 28, 2013 at 5:32 PM, Shane Gleason <sgleason at siu.edu> wrote:
>
> Hello everyone,
>
> I am working with lme4, specifically the glmer command. In a multilevel
> model I have an interaction term which is significant. However, with my
> discipline we stress that an interaction term cannot be evaluated by p value
> alone and one must reference a graphical display of the interaction, with
> confidence intervals drawn around it.
>
> That is to say if the interaction is X*Z then the interaction might be
> significant when X=1 and Z=3, but may not be significant if X=4 and Z=9.
>
> I have searched around and I can't seem to find any indication of how to
> graph out the interaction (though I see some references to it for lmer (but
> never glmer)). So, my question is two-part- 1: Does this assumption about
> how interaction terms work hold for MLMs? 2: If the answer to 1 is yes,
> does anyone know of software I can use to graph out these interactions?
>
> Thanks,
>
> Shane
>
> --
> Shane Gleason
> Doctoral Candidate
> Southern Illinois University:Carbondale
> Department of Political Science
> Faner 3172
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
> --
> Shane Gleason
> Doctoral Candidate
> Southern Illinois University:Carbondale
> Department of Political Science
> Faner 3172
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