superbPlot.pointindividualline {superb} | R Documentation |
superbPlot point and individual-line layout for within-subject design
Description
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:
Usage
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)
# 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)