Sequence Distribution Plot — ggseqdplot • ggseqplot

Function for rendering state distribution plots with ggplot2 wickham2016ggseqplot instead of base R's plot function that is used by TraMineR::seqplot gabadinho2011ggseqplot.

Usage

ggseqdplot(
  seqdata,
  no.n = FALSE,
  group = NULL,
  dissect = NULL,
  weighted = TRUE,
  with.missing = FALSE,
  border = FALSE,
  with.entropy = FALSE,
  linetype = "dashed",
  linecolor = "black",
  linewidth = 1,
  facet_ncol = NULL,
  facet_nrow = NULL,
  ...
)

Arguments

seqdata: State sequence object (class stslist) created with the TraMineR::seqdef function.
no.n: specifies if number of (weighted) sequences is shown (default is TRUE)
group: A vector of the same length as the sequence data indicating group membership. When not NULL, a distinct plot is generated for each level of group.
dissect: if "row" or "col" are specified separate distribution plots instead of a stacked plot are displayed; "row" and "col" display the distributions in one row or one column respectively; default is NULL
weighted: Controls if weights (specified in TraMineR::seqdef) should be used. Default is TRUE, i.e. if available weights are used
with.missing: Specifies if missing states should be considered when computing the state distributions (default is FALSE).
border: if TRUE bars are plotted with black outline; default is FALSE (also accepts NULL)
with.entropy: add line plot of cross-sectional entropies at each sequence position
linetype: The linetype for the entropy subplot (with.entropy==TRUE) can be specified with an integer (0-6) or name (0 = blank, 1 = solid, 2 = dashed, 3 = dotted, 4 = dotdash, 5 = longdash, 6 = twodash); ; default is "dashed"
linecolor: Specifies the color of the entropy line if with.entropy==TRUE; default is "black"
linewidth: Specifies the width of the entropy line if with.entropy==TRUE; default is 1
facet_ncol: Number of columns in faceted (i.e. grouped) plot
facet_nrow: Number of rows in faceted (i.e. grouped) plot
...: if group is specified additional arguments of ggplot2::facet_wrap such as "labeller" or "strip.position" can be used to change the appearance of the plot. Does not work if dissect is used

Value

A sequence distribution plot created by using ggplot2. If stored as object the resulting list object (of class gg and ggplot) also contains the data used for rendering the plot.

Details

Sequence distribution plots visualize the distribution of all states by rendering a series of stacked bar charts at each position of the sequence. Although this type of plot has been used in the life course studies for several decades (see blossfeld1987;textualggseqplot for an early application), it should be noted that the size of the different bars in stacked bar charts might be difficult to compare - particularly if the alphabet comprises many states wilke2019ggseqplot. This issue can be addressed by breaking down the aggregated distribution specifying the dissect argument. Moreover, it is important to keep in mind that this plot type does not visualize individual trajectories; instead it displays aggregated distributional information (repeated cross-sections). For a more detailed discussion of this type of sequence visualization see, for example, brzinsky-fay2014;textualggseqplot, fasang2014;textualggseqplot, and raab2022;textualggseqplot.

The function uses TraMineR::seqstatd to obtain state distributions (and entropy values). This requires that the input data (seqdata) are stored as state sequence object (class stslist) created with the TraMineR::seqdef function. The state distributions are reshaped into a a long data format to enable plotting with ggplot2. The stacked bars are rendered by calling geom_bar; if entropy = TRUE entropy values are plotted with geom_line. If the group or the dissect argument are specified the sub-plots are produced by using facet_wrap. If both are specified the plots are rendered with facet_grid.

The data and specifications used for rendering the plot can be obtained by storing the plot as an object. The appearance of the plot can be adjusted just like with every other ggplot (e.g., by changing the theme or the scale using + and the respective functions).

References

Author

Marcel Raab

Examples

# Use example data from TraMineR: actcal data set
data(actcal)

# We use only a sample of 300 cases
set.seed(1)
actcal <- actcal[sample(nrow(actcal), 300), ]
actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
actcal.seq <- seqdef(actcal, 13:24, labels = actcal.lab)
#>  [>] 4 distinct states appear in the data: 
#>      1 = A
#>      2 = B
#>      3 = C
#>      4 = D
#>  [>] state coding:
#>        [alphabet]  [label]  [long label] 
#>      1  A           A        > 37 hours
#>      2  B           B        19-36 hours
#>      3  C           C        1-18 hours
#>      4  D           D        no work
#>  [>] 300 sequences in the data set
#>  [>] min/max sequence length: 12/12

# state distribution plots; grouped by sex
# with TraMineR::seqplot
seqdplot(actcal.seq, group = actcal$sex)

# with ggseqplot
ggseqdplot(actcal.seq, group = actcal$sex)

# with ggseqplot applying a few additional arguments, e.g. entropy line
ggseqdplot(actcal.seq, group = actcal$sex,
           no.n = TRUE, with.entropy = TRUE, border = TRUE)


# break down the stacked plot to ease comparisons of distributions
ggseqdplot(actcal.seq, group = actcal$sex, dissect = "row")


# make use of ggplot functions for modifying the plot
ggseqdplot(actcal.seq) +
  scale_x_discrete(labels = month.abb) +
  labs(title = "State distribution plot", x = "Month") +
  guides(fill = guide_legend(title = "Alphabet")) +
  theme_classic() +
  theme(plot.title = element_text(size = 30,
                                  margin = margin(0, 0, 20, 0)),
    plot.title.position = "plot")
#> Scale for x is already present.
#> Adding another scale for x, which will replace the existing scale.