Plotting RESI Estimates and CIs — plot.resi • RESI

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 axis for the y-axis
automar: Logical, whether to automatically adjust the plotting margins to accommodate variable names. Default = `TRUE`
...: Other graphical parameters passed to plot and lines

Value

Returns a plot of RESI point estimates

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`.

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)