Wrapper function that creates one or more plots by sequentially calling functions from the graphics package.
apa_factorial_plot is the workhorse function that is called by apa_barplot, apa_beeplot, and apa_lineplot.
apa_factorial_plot(data, ...)# S3 method for default
apa_factorial_plot(data, id, factors = NULL, dv,
tendency = mean, dispersion = conf_int, level = 0.95,
fun_aggregate = mean, na.rm = TRUE, reference = 0, intercept = NULL,
args_x_axis = NULL, args_y_axis = NULL, args_title = NULL,
args_rect = NULL, args_points = NULL, args_lines = NULL,
args_swarm = NULL, args_error_bars = NULL, args_legend = NULL,
plot = NULL, jit = 0.3, xlab = NULL, ylab = NULL, main = NULL, ...)
# S3 method for afex_aov
apa_factorial_plot(data, tendency = mean,
dispersion = conf_int, fun_aggregate = mean, ...)
A data.frame that contains the data or an object of class afex_aov
Further arguments that will be passed to plot.window.
Character. Variable name that identifies subjects.
Character. A vector of up to four variable names that is used to stratify the data.
Character. The name of the dependent variable.
Closure. A function that will be used as measure of central tendency.
Closure. A function that will be used to construct error bars (i.e., whiskers). Defaults to
conf_int for 95% between-subjects confidence intervals. See details for more options, especially for within-subjects confidence intervals.
Numeric. Defines the width of the interval if confidence intervals are plotted. Defaults to 0.95.
for 95% confidence intervals. Ignored if dispersion is not a confidence-interval function. See details.
Closure. The function that will be used to aggregate observations within subjects and factors
before calculating descriptive statistics for each cell of the design. Defaults to mean.
Logical. Specifies if missing values are removed. Defaults to TRUE.
Numeric. A reference point that determines the y coordinate of the x axis. Useful if there exists a 'nil' value; defaults to0.
Numeric. Adds a horizontal line at height intercept to the plot. Can be either a single value or a matrix. For the matrix
case, multiple lines are drawn, where the dimensions of the matrix determine the number of lines to be drawn.
An optional list that contains further arguments that may be passed to axis for customising the x axis.
An optional list that contains further arguments that may be passed to axis for customising the y axis.
An optional list that contains further arguments that may be passed to title.
An optional list that contains further arguments that may be passed to rect.
An optional list that contains further arguments that may be passed to points.
An optional list that contains further arguments that may be passed to lines.
An optional list that contains further arguments to customize the points of the beeswarm.
An optional list that contains further arguments that may be passed to arrows.
An optional list that contains further arguments that may be passed to legend
Character. A vector specifying which elements of the plot should be plotted. Available options are
c("points", "error_bars", "bars", "swarms", "lines")
Numeric. Determines the amount of horizontal displacement. Defaults to 0.3, defaults to 0.4 if plot = "bars".
Character or expression. Label for x axis.
Character or expression. Label for y axis.
Character or expression. For up to two factors, simply specify the main title. If you stratify the data by more than two factors, either specify a single value that will be added to automatically generated main title, or specify an array of multiple titles, one for each plot area.
The measure of dispersion can be either conf_int for between-subjects confidence intervals, se for standard errors,
or any other standard function. For within-subjects confidence intervals, specify wsci or within_subjects_conf_int.
If between- or within-subjects confidence intervals are requested, you can also specify the area of the cumulative
distribution function that will be covered. For instance, if you want a 98% confidence interval, specify
level = 0.98. level defaults to 0.95.
Customisation of plot elements
apa_factorial_plot and its descendants apa_barplot, apa_lineplot, and apa_beeplot are wrapper functions that sequentially call
plot.new,
plot.window,
axis (once for x axis, once for y axis),
title for axis labels and titles,
rect for bars in barplots,
points for bee swarms,
lines for lines connecting central tendency points,
arrows for error bars,
points for tendency points,
legend for a legend, and
lines for intercepts.
These calls can be customised by setting the respective parameters args_***.
Other plots for factorial designs: apa_barplot,
apa_beeplot, apa_lineplot
# NOT RUN {
apa_factorial_plot(
data = npk
, id = "block"
, dv = "yield"
, factors = c("N", "P", "K")
, las = 1
, plot = c("error_bars", "points", "swarms")
, ylim = c(0, 100)
)
# }
Run the code above in your browser using DataLab