CODEWITHSUNDEEP
rplotregressionlme4mixed-models
rnorouzian
rnorouzian

Reputation: 7517

Plotting the predictions of a mixed model as a line in R

I'm trying to plot the predictions (predict()) of my mixed model below such that I can obtain my conceptually desired plot as a line below.

I have tried to plot my model's predictions, but I don't achieve my desired plot. Is there a better way to define predict() so I can achieve my desired plot?

library(lme4)

dat3 <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/dat3.csv')

m4 <- lmer(math~pc1+pc2+discon+(pc1+pc2+discon|id), data=dat3)

newdata <- with(dat3, expand.grid(pc1=unique(pc1), pc2=unique(pc2), discon=unique(discon)))

y <- predict(m4, newdata=newdata, re.form=NA)

plot(newdata$pc1+newdata$pc2, y)

enter image description here

Upvotes: 0

Views: 1991

Answers (2)

Magnus Nordmo
Magnus Nordmo

Reputation: 951

More sjPlot. See the parameter grid to wrap several predictors in one plot.

library(lme4)
library(sjPlot)
library(patchwork)

dat3 <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/dat3.csv')

m4 <- lmer(math~pc1+pc2+discon+(pc1+pc2+discon|id), data=dat3) # Does not converge

m4 <- lmer(math~pc1+pc2+discon+(1|id), data=dat3) # Converges

# To remove discon
a <- plot_model(m4,type = 'pred')[[1]]
b <- plot_model(m4,type = 'pred',title = '')[[2]]

a + b

enter image description here

Edit 1: I had some trouble removing the dropcon term within the sjPlot framework. I gave up and fell back on patchwork. I'm sure Daniel could knows the correct way.

Upvotes: 2

Oliver
Oliver

Reputation: 8602

As Magnus Nordmo suggest, this is very simple with sjPlot which has some predefined functions for these types of plot.

library(lme4)

dat3 <- read.csv('https://raw.githubusercontent.com/rnorouzian/e/master/dat3.csv')

m4 <- lmer(math~pc1+pc2+discon+(pc1+pc2+discon|id), data=dat3)

plot_model(m4, type = 'pred', terms = c('pc1', 'pc2'),
           ci.lvl = 0)

which gives the following result.

so-plot

This plot is designed to include different quantiles of the second term in terms over the axes of pc1 and pred. You could split up these plots and combine them using patchwork and the interval can be changed by using square brackets after the term in terms (eg pc1 [-10:1] for interval between -10 and 1).

Upvotes: 0

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