Problem:
I have produced an odds ratio plot (below) from the data frame called FID (below) using the plot_model() function in the sjPlot package, but the figure is too large for the plotting window.
I have two models involving: (1) FID_Model_1 (see figure 1); and (2) Mixed_FID_Model_1 (see figure 2). The mixed model contains the lowest AIC value, and, on the surface, appears to contain the best goodness of fit. However, arguably, the FID_Model_1 uses fewer degrees of freedom, and the Odds ratio plot (figure 1) illustrates this model has meaningful predictor values.
Therefore, I have attempted to produce Odds' ratio plots for both of these models to explore these relationships further - FID_Model_1 and the Mixed_FID_Model_1.
df AIC
FID_Model_1 13 17643.63
Mixed_FID_Model_1 22 12237.52
The idea is to show the relative importance of predictor variables in the mixed-effects glm() model called Mixed_FID_Model_1 (figure 2).
However, figure 2 is far too large to fit and into the plot window. I have tried resizing the plot window with different code syntax but I was unsuccessful.
If anyone is able to help, I would be deeply appreciative.
#####Open a plotter window
dev.new()
library(ggplot2)
library(sjmisc)
library(sjlabelled)
library(sjPlot)
##Plot the glm models
Mixed_FID_Model_1<-glm(FID~Year*Month, family=poisson, data=FID)
Model_FID_Model_1<-glm(FID~Year+Month, family=poisson, data=FID)
###Produce the Odds's Ratio Plots for models 1 and 2
##Open a plotting window
dev.new()
##Model 1 - Blue_Model_2
plot_model(Blue_Model_2,
show.values = TRUE, value.offset = .3)
##Open a plotting window
dev.new()
##Model 2 - Mixed_Blue_Model_1
plot_model(Mixed_Blue_Model_1,
show.values = TRUE, value.offset = .3)
Odds Ratio Plot for figure 1
Odds Ratio Plot for figure 2
Data frame: FID
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