plot.resi {RESI} | R Documentation |
Plotting RESI Estimates and CIs
Description
This function uses base graphics to plot robust effect size (RESI) estimates and confidence intervals from 'resi', 'summary_resi', and 'anova_resi' objects.
Usage
## S3 method for class 'resi'
plot(
x,
alpha = NULL,
ycex.axis = NULL,
yaxis.args = list(),
automar = TRUE,
...
)
Arguments
x |
Object of 'resi', 'summary_resi', or 'anova_resi' class |
alpha |
Numeric, desired alpha level for confidence intervals |
ycex.axis |
Numeric, scale specifically for the variable name labels |
yaxis.args |
List, other arguments to be passed to |
automar |
Logical, whether to automatically adjust the plotting margins to accommodate variable names. Default = 'TRUE' |
... |
Details
This function creates a forest-like plot with RESI estimates for each variable or factor. The size of the left margin will be automatically adjusted (and returned to original after plotting) unless 'automar = FALSE'. Additional graphics parameters will be passed to the main plot function, the confidence intervals. Arguments specifically for the y-axis (variable names) can be specified using 'yaxis.args'. To manually adjust the size of the y-axis labels without affecting the x-axis, the user can specify a value for 'ycex.axis'.
Value
Returns a plot of RESI point estimates
Examples
# create a resi object
resi_obj <- resi(lm(charges ~ region * age + bmi + sex, data = RESI::insurance),
nboot = 10)
# plot coefficients table, changing size of labels for both axes in the usual way
plot(resi_obj, cex.axis = 0.7)
# plot ANOVA table, changing the size of just the y-axis
plot(resi_obj, ycex.axis = 0.8)