Graphing interaction terms in LME4, glmer

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