Implicative Statistic Plot — ggseqimplicplot • ggseqplot

Function for plotting the implicative statistic of states by group and sequence position computed with TraMineRextras::seqimplic. The plot is rendered with ggplot2 (Wickham 2016) instead of base R's plot function that is used by TraMineRextras::plot.seqimplic.

Usage

ggseqimplicplot(
  seqdata = NULL,
  group = NULL,
  seqimplicobject = NULL,
  weighted = TRUE,
  with.missing = FALSE,
  conf.level = 0.95,
  linewidth = 1,
  facet_ncol = NULL,
  facet_nrow = NULL
)

Arguments

seqdata: State sequence object (class stslist) created with the TraMineR::seqdef function. Ignored if seqimplicobject is specified.
group: A vector of the same length as the sequence data indicating group membership. A distinct plot is generated for each level of group. Ignored if seqimplicobject is specified.
seqimplicobject: Object of class seqimplic generated with TraMineRextras::seqimplic. Either seqimplicobject or seqdata and group have to be specified.
weighted: Controls if weights (specified in TraMineR::seqdef) should be used. Default is TRUE, i.e. if available weights are used. Ignored if seqimplicobject is specified.
with.missing: Specifies if missing states should be considered when computing the implicative statistic (default is FALSE). Ignored if seqimplicobject is specified.
conf.level: Confidence level(s) shown as horizontal reference lines; default is 0.95. Several levels can be specified (e.g. c(0.95, 0.99)); NULL suppresses the reference lines.
linewidth: Specifies the width of the lines; 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

Value

A line plot of the implicative statistic created by using ggplot2. If stored as object the resulting list object (of class gg and ggplot) also contains the data (long format) used for rendering the plot.

Details

The implicative statistic measures how strongly membership in a group implies being in a certain state at a given sequence position. The function uses TraMineRextras::seqimplic to compute the statistic. Alternatively, an object of class seqimplic can be passed to the function.

Like in TraMineRextras::plot.seqimplic, the (sign-reversed) implicative statistic is shown for each state and position as line plot, with a separate plot for each group. Values below 0 are not shown. Values above the dotted reference line(s) indicate that the implication is significant at the respective confidence level.

The statistic is reshaped into a long data format and plotted with geom_line. The group-specific plots are produced by using facet_wrap. 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

Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis, Use R!, 2nd ed. edition. Springer, Cham. doi:10.1007/978-3-319-24277-4 .

Author

Marcel Raab

Examples

library(TraMineR)

# Use example data from TraMineR: mvad data set
data(mvad)
mvad.seq <- seqdef(mvad, 17:86)
#>  [>] 6 distinct states appear in the data: 
#>      1 = FE
#>      2 = HE
#>      3 = employment
#>      4 = joblessness
#>      5 = school
#>      6 = training
#>  [>] state coding:
#>        [alphabet]  [label]     [long label] 
#>      1  FE          FE          FE
#>      2  HE          HE          HE
#>      3  employment  employment  employment
#>      4  joblessness joblessness joblessness
#>      5  school      school      school
#>      6  training    training    training
#>  [>] 712 sequences in the data set
#>  [>] min/max sequence length: 70/70

# typical states of pupils with/without 5 or more GCSEs
# with TraMineRextras
mvad.si.gcse5eq <- TraMineRextras::seqimplic(mvad.seq, group = mvad$gcse5eq)
plot(mvad.si.gcse5eq, lwd = 3, conf.level = c(0.95, 0.99))


# with ggseqplot (using the seqimplic object ...)
ggseqimplicplot(seqimplicobject = mvad.si.gcse5eq,
                conf.level = c(0.95, 0.99))


# ... or using the sequence data and the group vector)
ggseqimplicplot(mvad.seq, group = mvad$gcse5eq,
                conf.level = c(0.95, 0.99), facet_ncol = 1)