superbPlot point and individual-line layout for within-subject design

Source: R/functionsPlotting_base.R

superbPlot comes with a few built-in templates for making the final plots. All produces ggplot objects that can be further customized. Additionally, it is possible to add custom-make templates (see vignette 6). The functions, to be "superbPlot-compatible", must have these parameters:

superbPlot.pointindividualline(
  summarydata,
  xfactor,
  groupingfactor,
  addfactors,
  rawdata,
  pointParams = list(),
  lineParams = list(),
  errorbarParams = list(),
  facetParams = list()
)

Arguments

summarydata

a data.frame with columns "center", "lowerwidth" and "upperwidth" for each level of the factors;

xfactor

a string with the name of the column where the factor going on the horizontal axis is given;

groupingfactor

a string with the name of the column for which the data will be grouped on the plot;

addfactors

a string with up to two additional factors to make the rows and columns panels, in the form "fact1 ~ fact2";

rawdata

always contains "DV" for each participants and each level of the factors

pointParams

(optional) list of graphic directives that are sent to the geom_bar layer

lineParams

(optional) list of graphic directives that are sent to the geom_bar layer

errorbarParams

(optional) list of graphic directives that are sent to the geom_superberrorbar layer

facetParams

(optional) list of graphic directives that are sent to the facet_grid layer

Value

a ggplot object

Examples

# This will make a plot with points and individual lines for each subject's scores
library(lsr)
#> Warning: package 'lsr' was built under R version 4.3.2

# we take the Orange built-in data.frame which has a within-subject design
names(Orange) <- c("Tree","age","circ")
# turn the data into a wide format
Orange.wide <- longToWide(Orange, circ ~ age)
# the identifier to each tree must be in a column called id
Orange.wide$id = Orange.wide$Tree

# Makes the plots two different way:
superbPlot( Orange.wide, WSFactors = "age(7)",
  variables = c("circ_118","circ_484","circ_664","circ_1004","circ_1231","circ_1372","circ_1582"),
  adjustments = list(purpose = "difference", decorrelation = "none"),
  plotStyle= "pointindividualline"
)


# if you extract the data with superbData, you can 
# run this layout directly
#processedData <- superbData(Orange.wide, WSFactors = "age(7)",
#  variables = c("circ_118","circ_484","circ_664","circ_1004","circ_1231","circ_1372","circ_1582"),
#  adjustments = list(purpose = "difference", decorrelation = "none"),
#)
#
#superbPlot.pointindividualline(processedData$summaryStatistic,
#   "age",
#   NULL,
#   ".~.",
#   processedData$rawData)