问题
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)
回答1:
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
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.
回答2:
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.
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).
来源:https://stackoverflow.com/questions/64978966/plotting-the-predictions-of-a-mixed-model-as-a-line-in-r