-----Original Message-----
From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-
project.org] On Behalf Of David Sidhu
Sent: Tuesday, December 11, 2018 7:29 PM
To: r-sig-mixed-models <r-sig-mixed-models at r-project.org>
Subject: [R-sig-ME] Plotting interactions while controlling for other
predictors.
I am interested in creating a plot of an interaction that accounts for
other variables present in a model.
I am attaching a reproducible example of my try so far, but I don?t
believe this is quite getting at what I?d like.
Essentially, I want to show the interaction between X2 and X3, while
controlling for X1.
Thank you very much.
Dave
set.seed(182)
require(data.table)
require(lme4)
require(ggplot2)
X1 = rnorm(1000)
X2 = rnorm(1000)
X3 = sample(1:3, size = 1000, replace = TRUE)
X3 <- as.factor(X3)
DV = rnorm(1000)
Item <- rep(1:10, times = 100)
Subject <- rep(1:100, each = 10)
d <- as.data.frame(cbind(X1, X2, X3, DV, Item, Subject))
m1 <- lmer(DV ~ X1 + X2*X3 + (1|Subject) + (1|Item), data = d)
d$Pred <- predict(m1)
library(ggplot2)
ggplot(d, aes(x = X2, y = Pred, col = factor(X3), group = X3)) +
geom_jitter(alpha = .2) + geom_smooth(method = "lm")
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David M. Sidhu, MSc
PhD Candidate
Department of Psychology
University of Calgary