5 Creating a single-case data plot

Plotting the data is a first important approach to analysis. After you create a scdf, the scplot() command helps you visualize the data. If the scdf contains more than one case, a multiple baseline plot is provided.

scplot is an add-on package to scan for visualizing single-case data. It replaces the plot.scdf() (or: plotSC()) function already included in scan (see Section D.1). For the time being, the “old” plot.scdf will be kept in future versions of scan.

5.1 Install `scplot`

splot is available from the CRAN repository. Execute install.packages("scplot") to install it.

If you are more adventures you can install the developmental version of scplot from github.The project is hosted at https://github.com/jazznbass/scplot. You can install it with devtools::install_github("jazznbass/scplot") from your R console. Make sure you have the package devtools installed before. The scplot package has to be compiled. When you are running R on a Windows machine you also have to install Rtools. Rtools is not an R package and can be downloaded from CRAN at https://cran.r-project.org/bin/windows/Rtools/.

The following chapter has been written with scplot version 0.3.9. If you have problems replicating the examples, please update to this version.

5.2 Basic principal

You start by providing an scdf object (see Section 3.2) to the scplot() function (e.g. scplot(exampleAB)). This already creates a default plot.

scplot(exampleAB)

Now you use a series of pipe-operators (%>% or |>) to apply functions that add elements and change characteristics of the resulting plot. For example:

scplot(exampleABC) |>
  add_title("My plot") |>
  set_xlabel("Days", color = "red", size = 1.3)

Here is an overview of possible functions:

Table 5.1: scplot functions

Function	What it does ...
set_dataline	Change the default dataline/ add an additional dataline
add_statline	Add a line or curve representing statistical parameters
add_arrow	Add an arrow to a specific case at a specific position
add_line	Add a line to a specific case
add_grid	Add a grid to the plot pannel
add_labels	Add value labels to each data-point
add_legend	Add a plot legend
add_marks	Mark specific data points of specific cases
add_ridge	Colour the area below the dataline
add_text	Add text to a specific case at a specific position
add_title	Add a title above the plot
add_caption	Add a caption below the plot
set_xlabel/ set_ylabel	Change and style axis labels
set_xaxis/ set_yaxis	Set the value range, increments etc. of the x- and y-axis
set_background	Set colour and texture of the plot background
set_panel	Set colour and texture of the plot panel
set_phasenames	Rename and style the phases
set_casenames	Rename and style the phases
set_separator	Style the vertical separator line between phases
set_theme	Apply a predefined visual theme
set_theme_element	Style specific elements of the plot
as_ggplot	Return a ggplot2 object for further processing
new_theme	Create/define a new visual theme

All text, line, dot, and area elements have a set of arguments to change visual characteristics.

Text arguments can be applied to the following functions: add_caption(), add_labels(), add_legend(), add_text(), add_title(), set_xlabel(), set_ylabel(), set_phasenames(), set_casenames().

Possible arguments are:

Table 5.2: Arguments for text elements

Argument	What it does ...
color	Change color. Either a color name or a color code (e.g. 'red' or '#110044').
size	Relativ size to the base text size.
family	The font ('serif', 'sans', 'mono')
face	The font face ("plain","bold","italic","bold.italic")
hjust	Horizontal alignment (0 = left, 0.5 = centered, 1 = right)
vjust	Vertical alignment (0 = upper, 0.5 = centered, 1 = lower)

Line arguments can be applied to the following functions: set_dataline(), add_statline(), add_line(), add_arrow(), add_ridge(), add_ridge(), set_xaxis(), set_yaxis(), set_separator().

Table 5.3: Arguments for line elements

Argument	What it does ...
color	Either a color name or a color code (e.g. 'red' or '#110044').
linewidth	Relativ width of the line.
linetype	Linetype ('solid', 'dashed', 'dotted')

Point arguments can be applied to the following functions: set_dataline(), add_statline(), add_marks(), add_arrow().

Table 5.4: Arguments for point elements

Argument	What it does ...
color	Either a color name or a color code (e.g. 'red' or '#110044').
size	Relative size.
shpae	Point shape.

5.3 Set and add datalines

The set_dataline function call

set_dataline(object, variable = NULL, line, point, type = “continuous”, …)

By default, the single-case plot will depict the main dependent variable as defined in the scdf object. For changing this default behaviour or adding a second data line, use the set_dataline() function. The function takes the argument variable (with the main dependent variable as a default) which must correspond to a variable name within the applied scdf.

scplot(exampleAB_add) |>
  set_dataline("depression")

Styling parameters like line and point colour will be set automatically based on the applied graphic theme. We will learn later about how to change and modify these themes. If you want to directly change the styling parameters, you can use the line and point arguments which take lists with styling parameters. For line, the parameters are colour, linewidth, linetype, lineend, and arrow. For point the parameters are colour, size, and shape.

scplot(exampleAB_add) |>
  set_dataline(
    line = list(colour = "darkred", linewidth = 2), 
    point = list(colour = "black", size = 3, shape = 15)
  )

5.4 Add statlines

The add_statline function call

add_statline(object, stat = c(“mean”, “median”, “min”, “max”, “quantile”, “sd”, “mad”, “trend”, “trendA”, “trendA theil-sen”, “moving mean”, “moving median”, “loreg”, “lowess”, “loess”), phase = NULL, color = NULL, linewidth = NULL, linetype = NULL, variable = NULL, …)

5.4.1 Lines indicating a constant for each phase

Possible functions: mean, min, max, median, sd, quantile

scplot(exampleABC) |>
  add_statline("mean") |>
  add_statline("max") |>
  add_statline("min") |> 
  add_statline("median")

5.4.2 Lines indicating a constant for a specific phase

Set the phase argument with one or multiple phase-names or phase-numbers

Possible functions: mean, min, max, quantile

The following example sets a line with the mean of phase A, the maximum of phases B and C and the minimum of phases 2 and 3:

scplot(exampleABC) |>
  add_statline("mean", phase = "A") |>
  add_statline("max", phase = c("B", "C")) |>
  add_statline("min", phase = c(2, 3)) |> add_legend()

5.4.3 Trend-lines

trend (separate trend-line for each phase), trendA (extrapolated trend-line of first phase):

scplot(exampleABC) |>
  add_statline("trend") |>
  add_statline("trendA")

You scan specify various methods with the method argument for the trendA statistic:

scplot(exampleABC) |> 
  add_statline("trendA") |> 
  add_statline("trendA", method = "theil-sen") |> 
  add_statline("trendA", method = "bisplit") |> 
  add_statline("trendA", method = "trisplit") |> 
  add_legend()

For the trend statistic you can set method = "theil-sen" for median based Theil-Sen slope lines.

5.4.4 Smoothed curves

Possible functions: moving mean, moving median, loess, lowess:

scplot(exampleABC) |>
  add_statline("loess") |>
  add_statline("moving mean")

5.4.5 Refine with additional arguments

Some of the statistics allow additional arguments to specify parameters:

Statistic	Argument	What it does …
mean	trim	Trims the mean. `trim = 0.10` calculates a 10$ trimmed mean.
quantile	probs	Probability. `probs = 0.25` calculates the 25% quantile.
moving mean, moving median	lag	Lag surrounding the estimated value. `lag = 2` will calculate mean or median based on the two values before and after the to be replaced value.
loess	span	Proportion of the surrounding point to estimate a value.
lowess	f	Proportion of the surrounding point to estimate a value.

scplot(exampleABC) |>
  add_statline("moving mean", lag = 1) |>
  add_statline("quantile", probs = 0.75)

5.4.6 Specify data-line

If you do not specify the variable argument, the default first data-line is addressed.

scplot(exampleAB_add) |>
  set_dataline("cigarrets") |>
  add_statline("mean", variable = "cigarrets") |>
  add_statline("trend")

5.5 Annotate and mark

5.5.1 Add marks

The positions argument can take a numeric vector:

scplot(exampleABC) |>
  add_marks(case = 1, positions = c(7, 12)) |>
  add_marks(case = 3, positions = c(3, 17), color = "blue", size = 7)

The positions argument can also be a string containing a logical expression. This will be evaluated and the respective positions will be marked.

scplot(exampleABC) |>
  add_marks(case = 1, positions = "mt > 15") |>
  add_marks(case = 2, positions = 'phase == "B"', color = "green", size = 5) |>
  add_marks(case = 3, positions = "values > quantile(values, probs = 0.80)", color = "blue", size = 7) |>
  add_marks(case = "all", positions = "values < quantile(values, probs = 0.20)", color = "yellow", size = 7) |>
  add_caption("Note.
red: mt > 15 in case 1; 
green: phase 'B' in case 2; 
blue: values > 80% quantile of case 3; 
yellow: values < 20% quantile of all cases")

And the positions argument can take the results from a scan outlier analyses and mark the positions of the outliers of each case:

scplot(exampleABC_outlier) |> 
  add_marks(positions = outlier(exampleABC_outlier), size = 3)

5.5.2 Add text

scplot(exampleABC) |>
  add_text("Here!", case = 2, x = 10, y = 80, color = "red")

5.5.3 Add line

Draw lines either by providing starting (x0 and y0) an end coordinates (x1 and y1) or a horizontal (hline) or vertical (vline) position:

scplot(exampleABC) |>
  add_line(case = 1, x0 = 6, y0 = 90, x1 = 3, y1 = 63, color = "red") |> 
  add_line(case = 2, hline = 80, color = "blue") |> 
  add_line(case = 3, vline = 15, color = "green")

Draw an arrow:

scplot(exampleABC) |>
  add_arrow(case = 1, x0 = 6, y0 = 90, x1 = 3, y1 = 63) |>
  add_text("Problem", case = 1, x = 6, y = 94, color = "red", size = 1, hjust = 0 )

5.6 Change appearance of basic plot elements

5.6.1 Data line

scplot(exampleABC) |>
  set_dataline(color = "blue", linewidth = 1, linetype = "dotted", 
               point = list(colour = "red", size = 1, shape = 2) )

# Equivalent_
# scplot(exampleABC) |>
#   set_dataline(line = list(colour = "blue", size = 1, linetype = "dotted"), 
#                point = list(colour = "red", size = 1, shape = 2))

5.6.2 Background

scplot(exampleABC) |>
  set_background(fill = "grey90", color = "black", size = 2)

5.6.3 Panel

scplot(exampleABC) |>
  set_panel(fill = "tan1", color = "palevioletred", size = 2)

5.6.4 A different panel color for each phase

Note: The colors are 50% transparent. So they might appear different.

scplot(exampleABC) |>
  set_panel(fill = c("grey80", "white", "blue4"))

5.7 Themes

Themes are complete styles that define various elements of a plot.

Function set_theme("theme_name")

Possible themes:

basic, grid, default, small, tiny, big, minimal, dark, sienna, phase_color, phase_shade, grid2, illustration

5.7.1 An overview

5.7.2 Combine themes

When providing multiple themes the order is important as the latter overwrites styles of the former.

scplot(exampleABC) |>
  set_theme("sienna", "minimal", "small", "phase_color")

5.7.3 Set base text

The base text size is the absolute size. All other text sizes are relative to this base text size.

scplot(exampleAB_decreasing$Peter) |>
  set_base_text(colour = "blue", family = "serif", face = "italic", size = 14)

5.8 Add title and caption

scplot(exampleAB_decreasing) |>
  add_title("A new plot", color = "darkblue", size = 1.3) |>
  add_caption("Note. What a nice plot!", face = "italic", color = "darkred")

5.9 Add a legend

scplot(exampleABC) |>
  add_statline("mean", color = "darkred") |>
  add_statline("min", phase = "B", linewidth = 0.2, color = "darkblue") |>
  add_legend()

and set specific elements

scplot(exampleABC) |>
  add_statline("mean", color = "darkred") |>
  add_legend(
    position = "left", 
    title = list(size = 12, face = "italic"),
    background = list(fill = "grey95", colour = "black")
  )

5.10 Customize axis settings

When axis ticks are to close together set the increment argument to leave additional space (e.g. increment = 2 will annotate every other value). When you set increment_from = 0 an additional tick will be set at 1 although counting of the increments will start at 0.

scplot(exampleA1B1A2B2) |> 
  set_xaxis(increment_from = 0, increment = 5, 
            color = "darkred", size = 0.7, angle = -90) |>
  set_yaxis(limits = c(0, 50), size = 0.7, color = "darkred")

5.11 Customize axis labels

scplot(exampleA1B1A2B2) |> 
  set_ylabel("Score", color = "darkred", angle = 0) |>
  set_xlabel("Session", color = "darkred")

5.12 Change Casenames

scplot(exampleA1B1A2B2) |>
  set_casenames(c("A", "B", "C"), color = "darkblue", size = 1)

Casenames as strips:

scplot(exampleA1B1A2B2) |>
  set_casenames(position = "strip", 
                background = list(fill = "lightblue"))

5.13 Add value labels

scplot(exampleABC) |> 
  add_labels(text = list(color = "black", size = 0.7), 
             background = list(fill = "grey98"), nudge_y = 7)

Warning: Removed 1 rows containing missing values (`geom_label()`).

If you set the nudge_y argument to 0, the label will be set on-top the datapoints:

scplot(exampleABC) |> 
  add_labels(text = list(color = "black", size = 0.7), 
             background = list(fill = "grey98"), nudge_y = 0)

5.14 Add a ridge

scplot(exampleAB_mpd) |> 
  add_ridge("grey50")

5.15 Extending scplot with ggplot2

scplot() generates ggplot2 objects. You can keep the ggplot2 object and assign it into a new object with the as_ggplot() function. Thereby, you can use many ggplot2 functions to rework your graphics:

p1 <- scplot(byHeart2011$`Lisa (Turkish)`) |> 
        set_theme("minimal") |>
        as_ggplot()
p2 <- scplot(byHeart2011$`Patrick (Spanish)`) |> 
        set_theme("minimal") |> 
        as_ggplot()
p3 <- scplot(byHeart2011$`Anna (Twi)`) |> 
        set_theme("minimal") |> 
        as_ggplot()
p4 <- scplot(byHeart2011$`Melanie (Swedish)`) |> 
        set_theme("minimal") |> 
        as_ggplot()

library(patchwork)
p1 + p2 + p3 + p4 + plot_annotation(tag_levels = "a", tag_suffix =  ")")

5.16 Complexs examples

Here are some more complex examples

scplot(example_A24) |> 
  add_statline("lowess", linewidth = 1.5) |>
  add_statline("loess", linewidth = 1.5) |>
  add_statline("moving mean", lag = 3, linewidth = 1.5) |>
  set_xaxis(size = 0.8, angle = 35) |>
  set_dataline(point = "none") |>
  add_legend(position = c(0.8, 0.75), background = list(color = "grey50")) |>
  set_phasenames(c("no speedlimit", "with speedlimit"), 
                 position = "left", hjust = 0, vjust = 1) |>
  set_casenames(position = "none") |>
  add_title("Effect of a speedlimit on the A24") |>
  add_caption("Note: Moving mean calculated with lag three", face = 3, size = 1) |>
  add_ridge(color = "lightblue")

scplot(exampleAB_add) |>
  set_dataline("cigarrets", point = list(size = 1)) |>
  add_statline("trend", linetype = "dashed") |>
  add_statline("mean", variable = "cigarrets", color = "darkred") |>
  add_marks(positions = c(14,20), size = 3, variable = "cigarrets")|>
  add_marks(positions = "cigarrets > quantile(cigarrets, 0.75)", size = 3) |>
  set_xaxis(increment = 5) |>
  set_phasenames(color = NA) |>
  set_casenames(position = "strip") |>
  add_legend(
    section_labels = c("", ""),
    labels = c(NA, NA, "Trend of wellbeing", "Mean of cigarrets"),
    text = list(face = 3)
  ) |>
  set_panel(fill = c("lightblue", "grey80")) |>
  add_ridge(color = "snow", variable = "cigarrets") |>
  add_labels(variable = "cigarrets", nudge_y = 2, 
             text = list(color = "blue", size = 0.5)) |>
  add_labels(nudge_y = 2, text = list(color = "black", size = 0.5),
             background = list(fill = "white"))

Warning: Removed 1 rows containing missing values (`geom_label()`).

scplot(exampleA1B1A2B2) |> 
  set_xaxis(increment = 4, size = 0.7) |>
  set_yaxis(color = "sienna3") |>
  set_ylabel("Points", color = "sienna3", angle = 0) |>
  set_xlabel("Weeks", size = 1, color = "brown") |>
  add_title("Points by week", color = "sienna4", face = 3) |>
  add_caption("Note: An extensive Example.",
              color = "black", size = 1, face = 3) |>
  set_phasenames(c("Baseline", "Intervention", "Fall-Back", "Intervention_2"), 
                 size = 0) |>
  add_ridge(scales::alpha("lightblue", 0.5)) |>
  set_casenames(labels = sample_names(3), color = "steelblue4", size = 0.7) |>
  set_panel(fill = c("grey80", "grey95"), color = "sienna4") |>
  add_grid(color = "grey85", linewidth = 0.1) |>
  set_dataline(size = 0.5, linetype = "solid", 
               point = list(colour = "sienna4", size = 0.5, shape = 18)) |>
  add_labels(text = list(color = "sienna", size = 0.7), nudge_y = 4) |>
  set_separator(size = 0.5, linetype = "solid", color = "sienna") |>
  add_statline(stat = "trendA", color = "tomato2") |>
  add_statline(stat = "max", phase = c(1, 3), linetype = "dashed") |>
  add_marks(case = 1:2, positions = 14, color = "red3", size = 2, shape = 4) |>
  add_marks(case = "all", positions = "values < quantile(values, 0.1)", 
            color = "blue3", size = 1.5) |>
  add_marks(positions = outlier(exampleABAB), color = "brown", size = 2) |>
  add_text(case = 1, x = 5, y = 35, label = "Interesting", 
           color = "darkgreen", angle = 20, size = 0.7) |>
  add_arrow(case = 1, 5, 30, 5, 22, color = "steelblue") |>
  set_background(fill = "white") |>
  add_legend() |>
  set_theme("basic") |>
  set_theme_element(panel.spacing.y = unit(0, "points"))

Warning: Removed 6 rows containing missing values (`geom_text()`).

Adding bars is a bit more complicated:

Set the type argument to "bar"
Extend the limits of the x-axis by 1 (here from 0 to 41)
Set the left margin of the x-axis to 0 with the expand argument.

scplot(exampleAB_add) |>
  set_xaxis(expand = c(0, 0), limits = c(0, 41)) |>
  set_dataline("cigarrets", type = "bar", linewidth = 0.6, point = "none") |>
  add_statline("mean", variable = "cigarrets", color = "darkred") |>
  add_statline("trend", linetype = "dashed") |>
  set_casenames(position = "strip")

5.1 Install scplot

5.2 Basic principal

5.3 Set and add datalines

5.4 Add statlines

5.4.1 Lines indicating a constant for each phase

5.4.2 Lines indicating a constant for a specific phase

5.4.3 Trend-lines

5.4.4 Smoothed curves

5.4.5 Refine with additional arguments

5.4.6 Specify data-line

5.5 Annotate and mark

5.5.1 Add marks

5.5.2 Add text

5.5.3 Add line

5.6 Change appearance of basic plot elements

5.6.1 Data line

5.6.2 Background

5.6.3 Panel

5.6.4 A different panel color for each phase

5.7 Themes

5.7.1 An overview

5.7.2 Combine themes

5.7.3 Set base text

5.8 Add title and caption

5.9 Add a legend

5.10 Customize axis settings

5.11 Customize axis labels

5.12 Change Casenames

5.13 Add value labels

5.14 Add a ridge

5.15 Extending scplot with ggplot2

5.16 Complexs examples

5.1 Install `scplot`