View source: R/levelComparePlot.R
levelComparePlot | R Documentation |
Plots the line of best for the relationship between two variables accounting for nesting and not accounting for nesting.
levelComparePlot( model, x, y, grouping, dataset, paneled = TRUE, select = c("select"), center = FALSE, xlab = x, ylab = y, glab = grouping, plot_titles = c("Scatter Plot", "Scatter Plot by Group") )
model |
A linear mixed-effects model of class lmerMod or lmerModLmerTest. |
x |
Predictor variable. |
y |
Outcome variable. |
grouping |
Grouping variable. |
dataset |
A dataset containing the predictor, outcome, and grouping variables. |
paneled |
A logical value indicating whether the plot accounting for nesting should be split into panels. |
select |
A vector indicating the index of the groups to be included in the plots. |
center |
A logical value indicating whether the x variable should be centered |
xlab |
Character vector specifying the horizontal axis label. |
ylab |
Character vector specifying the vertical axis label. |
glab |
Character vector specifying the legend title for the plot accounting for nesting. |
plot_titles |
Character vectors specifying the titles for the plots. |
# Gaussian ## Read in data data(instruction) ## Create model mod <- lme4::lmer(mathgain ~ mathkind + (1 | classid), data = instruction) ## Generate plots levelComparePlot(mod, x = "mathkind", y = "mathgain", grouping = "classid", dataset = instruction) # Logistic ## Read in data data(reporting) reporting$final.sample.size <- scale(as.numeric(reporting$final.sample.size)) reporting$mention.outliers <- ifelse(reporting$mention.outliers=="No",0,1) mod <- lme4::glmer(mention.outliers ~ final.sample.size + (1 | Journal), data = reporting, family = "binomial") levelComparePlot(mod, x = "final.sample.size", y = "mention.outliers", grouping = "Journal", dataset = reporting, paneled = FALSE)
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