[R-sig-ME] Visualizing three-way interaction

[Houslay, Tom]

Hi Klemens,


You probably have all the answers you need now, but just in case they are at all useful then I have a little series of posts on my website about visualising 3-way interactions using various methods:

2 continuous, 1 categorical:
https://tomhouslay.com/2015/06/02/understanding-3-way-interactions-between-continuous-and-categorical-variables-part-ii-2-cats-1-con/

1 continuous, 2 categorical:
https://tomhouslay.com/2014/09/06/understanding-3-way-interactions-between-continuous-and-categorical-variables-small-multiples/

3 continuous:
https://tomhouslay.com/2014/03/21/understanding-3-way-interactions-between-continuous-variables/

Some of these are a little old and don't take advantage of better functions in R (that didn't exist or I was unaware of at the time!), but might be helpful for ideas on different ways of plotting things. These are generally using standard regression models, but predict/broom etc can be used to average over random effects (eg using 're.form = NA' in the predict.merMod function).

Good luck with your plots!

Cheers

Tom

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Subject: R-sig-mixed-models Digest, Vol 124, Issue 12


Message: 1
Date: Wed, 12 Apr 2017 11:41:00 +0200
From: Klemens Kn?ferle <knoeferle at gmail.com>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] LMER: Visualizing three-way interaction
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Hi all,

I'm trying to visualize a three-way interaction from a rather complex
linear mixed model in R (lmer function from the lme4 package; the model has
a complex random-effects structure). The interaction consists of two
continuous variables and one categorical variable (two experimental
conditions).

So far, I have graphed the interaction via two 3D-surface plots using
visreg2d from the visreg package. But my reviewers found these plots
confusing and asked for a different illustration, such as conditional
coefficient plots (i.e., plots of the strength of coefficient 1 as
coefficient 2 increases).

I've tried to find a package that allows me to create these kind of plots,
but failed. The existing packages only allow coefficient plots for two-way
interactions (for instance the interplot package;
https://cran.r-project.org/web/packages/interplot/vignettes/interplot-vignette.html).
That means I only get a conditional coefficient plot of the two-way
interaction, collapsed across both levels of the categorical variable.

Is there a package for my case? If not, I probably have to manually extract
fitted values from my model (e.g., using broom) and somehow plot them in
ggplot2. But I don't really know how to do this, whether or not to take
into account random effects (and how), etc. Any ideas would be much
appreciated...

Klemens Kn?ferle, Ph.D.
Associate Professor - Department of Marketing
BI Norwegian Business School
Visiting address: Nydalsveien 37, 0484 Oslo

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