Easy scatter plots over multiple times (T1, T2, T3) — plot_means_over

Make nice scatter plots over multiple times (T1, T2, T3) easily.

Usage

plot_means_over_time(
  data,
  response,
  group,
  groups.order = "none",
  ci_type = "within",
  error_bars = TRUE,
  ytitle = NULL,
  legend.title = "",
  legend.position = "right",
  significance_stars,
  significance_stars_x,
  significance_stars_y,
  significance_bars_x,
  line_width = 3,
  point_size = 4,
  print_table = FALSE,
  verbose = FALSE,
  facet = NULL
)

Arguments

data: The data frame.
response: The dependent variable to be plotted (e.g., c("variable_T1", "variable_T2", "variable_T3"), etc.).
group: The group by which to plot the variable
groups.order: Specifies the desired display order of the groups on the legend. Either provide the levels directly, or a string: "increasing" or "decreasing", to order based on the average value of the variable on the y axis, or "string.length", to order from the shortest to the longest string (useful when working with long string names). "Defaults to "none".
ci_type: Character string specifying the type of confidence interval to use. Options are "within" (default) for within-subject adjusted CIs using the Morey (2008) correction, or "between" for regular between-subject CIs. Use "between" for simulated data or non-repeated-measures designs.
error_bars: Logical, whether to include 95% confidence intervals for means.
ytitle: An optional x-axis label, if desired. If NULL, will take the variable name of the first variable in response, and keep only the part of the string before an underscore or period.
legend.title: The desired legend title.
legend.position: The position of the legend. Can be "right" (default), "left", "top", "bottom", or "none" to hide the legend. Useful for positioning the legend at the bottom for very wide figures.
significance_stars: Vetor of significance stars to display on the plot (e.g,. c("*", "**", "***")).
significance_stars_x: Vector of where on the x-axis significance stars should appear on the plot (e.g., c(2.2, 3.2, 4.2)).
significance_stars_y: Vector of where on the y-axis significance stars should appear on the plot. The logic here is different than previous arguments. Rather than providing actual coordinates, we provide a list object with structure group 1, group 2, and time of comparison, e.g., list(c("group1", "group2", time = 2), c("group1", "group3", time = 3), c("group2", "group3", time = 4)).
significance_bars_x: Vector of where on the x-axis vertical significance bars should appear on the plot (e.g., c(2:4)).
line_width: Numeric. Line thickness used in geom_line(). Defaults to 3. Can be reduced for publication figures or increased for presentation slides.
point_size: Numeric. Point size used in geom_point(). Defaults to 4. Adjust to improve readability depending on output format.
print_table: Logical, whether to also print the computed table.
verbose: Logical, whether to also print a note regarding the meaning of the error bars.
facet: The variable by which to facet grid.

Value

A scatter plot of class ggplot.

Details

By default, error bars are calculated using the method of Morey (2008) through Rmisc::summarySEwithin(), but raw means are plotted instead of the normed means. For more information, visit: http://www.cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2).

Use ci_type = "between" for regular (between-subject) confidence intervals when working with simulated data or non-repeated-measures designs.

References

Morey, R. D. (2008). Confidence intervals from normalized data: A correction to Cousineau (2005). Tutorials in Quantitative Methods for Psychology, 4(2), 61-64. doi:10.20982/tqmp.04.2.p061

Examples

data <- mtcars
names(data)[6:3] <- paste0("T", 1:4, "_var")
plot_means_over_time(
  data = data,
  response = names(data)[6:3],
  group = "cyl",
  groups.order = "decreasing",
  facet = "am"
)
#> Automatically converting the following non-factors to factors: am


# Add significance stars/bars
plot_means_over_time(
  data = data,
  response = names(data)[6:3],
  group = "cyl",
  significance_bars_x = c(3.15, 4.15),
  significance_stars = c("*", "***"),
  significance_stars_x = c(3.25, 4.5),
  significance_stars_y = list(
    c("4", "8", time = 3),
    c("4", "8", time = 4)
  )
)

# significance_stars_y: List with structure: list(c("group1", "group2", time))