plot.CMA_per_episode {AdhereR}R Documentation

Plot CMA_per_episode and CMA_sliding_window objects.

Description

Plots the event data and the estimated CMA per treatment episode and sliding window, respectively.

Usage

## S3 method for class 'CMA_per_episode'
plot(
  x,
  patients.to.plot = NULL,
  duration = NA,
  align.all.patients = FALSE,
  align.first.event.at.zero = TRUE,
  show.period = c("dates", "days")[2],
  period.in.days = 90,
  show.legend = TRUE,
  legend.x = "right",
  legend.y = "bottom",
  legend.bkg.opacity = 0.5,
  legend.cex = 0.75,
  legend.cex.title = 1,
  cex = 1,
  cex.axis = 0.75,
  cex.lab = 1,
  show.cma = TRUE,
  xlab = c(dates = "Date", days = "Days"),
  ylab = c(withoutCMA = "patient", withCMA = "patient (& CMA)"),
  title = c(aligned = "Event patterns (all patients aligned)", notaligned =
    "Event patterns"),
  col.cats = rainbow,
  unspecified.category.label = "drug",
  medication.groups.to.plot = NULL,
  medication.groups.separator.show = TRUE,
  medication.groups.separator.lty = "solid",
  medication.groups.separator.lwd = 2,
  medication.groups.separator.color = "blue",
  medication.groups.allother.label = "*",
  lty.event = "solid",
  lwd.event = 2,
  pch.start.event = 15,
  pch.end.event = 16,
  plot.events.vertically.displaced = TRUE,
  print.dose = FALSE,
  cex.dose = 0.75,
  print.dose.outline.col = "white",
  print.dose.centered = FALSE,
  plot.dose = FALSE,
  lwd.event.max.dose = 8,
  plot.dose.lwd.across.medication.classes = FALSE,
  col.na = "lightgray",
  col.continuation = "black",
  lty.continuation = "dotted",
  lwd.continuation = 1,
  print.CMA = TRUE,
  CMA.cex = 0.5,
  plot.CMA = TRUE,
  plot.CMA.as.histogram = TRUE,
  plot.partial.CMAs.as = c("stacked", "overlapping", "timeseries")[1],
  plot.partial.CMAs.as.stacked.col.bars = "gray90",
  plot.partial.CMAs.as.stacked.col.border = "gray30",
  plot.partial.CMAs.as.stacked.col.text = "black",
  plot.partial.CMAs.as.timeseries.vspace = 7,
  plot.partial.CMAs.as.timeseries.start.from.zero = TRUE,
  plot.partial.CMAs.as.timeseries.col.dot = "darkblue",
  plot.partial.CMAs.as.timeseries.col.interval = "gray70",
  plot.partial.CMAs.as.timeseries.col.text = "firebrick",
  plot.partial.CMAs.as.timeseries.interval.type = c("none", "segments", "arrows",
    "lines", "rectangles")[2],
  plot.partial.CMAs.as.timeseries.lwd.interval = 1,
  plot.partial.CMAs.as.timeseries.alpha.interval = 0.25,
  plot.partial.CMAs.as.timeseries.show.0perc = TRUE,
  plot.partial.CMAs.as.timeseries.show.100perc = FALSE,
  plot.partial.CMAs.as.overlapping.alternate = TRUE,
  plot.partial.CMAs.as.overlapping.col.interval = "gray70",
  plot.partial.CMAs.as.overlapping.col.text = "firebrick",
  CMA.plot.ratio = 0.1,
  CMA.plot.col = "lightgreen",
  CMA.plot.border = "darkgreen",
  CMA.plot.bkg = "aquamarine",
  CMA.plot.text = CMA.plot.border,
  highlight.followup.window = TRUE,
  followup.window.col = "green",
  highlight.observation.window = TRUE,
  observation.window.col = "yellow",
  observation.window.opacity = 0.3,
  alternating.bands.cols = c("white", "gray95"),
  bw.plot = FALSE,
  force.draw.text = FALSE,
  min.plot.size.in.characters.horiz = 0,
  min.plot.size.in.characters.vert = 0,
  max.patients.to.plot = 100,
  export.formats = NULL,
  export.formats.fileprefix = "AdhereR-plot",
  export.formats.height = NA,
  export.formats.width = NA,
  export.formats.save.svg.placeholder = TRUE,
  export.formats.svg.placeholder.type = c("jpg", "png", "webp")[2],
  export.formats.svg.placeholder.embed = FALSE,
  export.formats.html.template = NULL,
  export.formats.html.javascript = NULL,
  export.formats.html.css = NULL,
  export.formats.directory = NA,
  generate.R.plot = TRUE,
  suppress.warnings = FALSE,
  ...
)

## S3 method for class 'CMA_sliding_window'
plot(
  x,
  patients.to.plot = NULL,
  duration = NA,
  align.all.patients = FALSE,
  align.first.event.at.zero = TRUE,
  show.period = c("dates", "days")[2],
  period.in.days = 90,
  show.legend = TRUE,
  legend.x = "right",
  legend.y = "bottom",
  legend.bkg.opacity = 0.5,
  legend.cex = 0.75,
  legend.cex.title = 1,
  cex = 1,
  cex.axis = 0.75,
  cex.lab = 1,
  show.cma = TRUE,
  xlab = c(dates = "Date", days = "Days"),
  ylab = c(withoutCMA = "patient", withCMA = "patient (& CMA)"),
  title = c(aligned = "Event patterns (all patients aligned)", notaligned =
    "Event patterns"),
  col.cats = rainbow,
  unspecified.category.label = "drug",
  medication.groups.to.plot = NULL,
  medication.groups.separator.show = TRUE,
  medication.groups.separator.lty = "solid",
  medication.groups.separator.lwd = 2,
  medication.groups.separator.color = "blue",
  medication.groups.allother.label = "*",
  lty.event = "solid",
  lwd.event = 2,
  pch.start.event = 15,
  pch.end.event = 16,
  plot.events.vertically.displaced = TRUE,
  print.dose = FALSE,
  cex.dose = 0.75,
  print.dose.outline.col = "white",
  print.dose.centered = FALSE,
  plot.dose = FALSE,
  lwd.event.max.dose = 8,
  plot.dose.lwd.across.medication.classes = FALSE,
  col.na = "lightgray",
  col.continuation = "black",
  lty.continuation = "dotted",
  lwd.continuation = 1,
  print.CMA = TRUE,
  CMA.cex = 0.5,
  plot.CMA = TRUE,
  plot.CMA.as.histogram = TRUE,
  plot.partial.CMAs.as = c("stacked", "overlapping", "timeseries")[1],
  plot.partial.CMAs.as.stacked.col.bars = "gray90",
  plot.partial.CMAs.as.stacked.col.border = "gray30",
  plot.partial.CMAs.as.stacked.col.text = "black",
  plot.partial.CMAs.as.timeseries.vspace = 7,
  plot.partial.CMAs.as.timeseries.start.from.zero = TRUE,
  plot.partial.CMAs.as.timeseries.col.dot = "darkblue",
  plot.partial.CMAs.as.timeseries.col.interval = "gray70",
  plot.partial.CMAs.as.timeseries.col.text = "firebrick",
  plot.partial.CMAs.as.timeseries.interval.type = c("none", "segments", "arrows",
    "lines", "rectangles")[2],
  plot.partial.CMAs.as.timeseries.lwd.interval = 1,
  plot.partial.CMAs.as.timeseries.alpha.interval = 0.25,
  plot.partial.CMAs.as.timeseries.show.0perc = TRUE,
  plot.partial.CMAs.as.timeseries.show.100perc = FALSE,
  plot.partial.CMAs.as.overlapping.alternate = TRUE,
  plot.partial.CMAs.as.overlapping.col.interval = "gray70",
  plot.partial.CMAs.as.overlapping.col.text = "firebrick",
  CMA.plot.ratio = 0.1,
  CMA.plot.col = "lightgreen",
  CMA.plot.border = "darkgreen",
  CMA.plot.bkg = "aquamarine",
  CMA.plot.text = CMA.plot.border,
  highlight.followup.window = TRUE,
  followup.window.col = "green",
  highlight.observation.window = TRUE,
  observation.window.col = "yellow",
  observation.window.opacity = 0.3,
  alternating.bands.cols = c("white", "gray95"),
  bw.plot = FALSE,
  force.draw.text = FALSE,
  min.plot.size.in.characters.horiz = 0,
  min.plot.size.in.characters.vert = 0,
  max.patients.to.plot = 100,
  export.formats = NULL,
  export.formats.fileprefix = "AdhereR-plot",
  export.formats.height = NA,
  export.formats.width = NA,
  export.formats.save.svg.placeholder = TRUE,
  export.formats.svg.placeholder.type = c("jpg", "png", "webp")[2],
  export.formats.svg.placeholder.embed = FALSE,
  export.formats.html.template = NULL,
  export.formats.html.javascript = NULL,
  export.formats.html.css = NULL,
  export.formats.directory = NA,
  generate.R.plot = TRUE,
  suppress.warnings = FALSE,
  ...
)

Arguments

x

A CMA0 or derived object, representing the CMA to plot

patients.to.plot

A vector of strings containing the list of patient IDs to plot (a subset of those in the cma object), or NULL for all

duration

A number, the total duration (in days) of the whole period to plot; in NA it is automatically determined from the event data such that the whole dataset fits.

align.all.patients

Logical, should all patients be aligned (i.e., the actual dates are discarded and all plots are relative to the earliest date)?

align.first.event.at.zero

Logical, should the first event be placed at the origin of the time axis (at 0)?

show.period

A string, if "dates" show the actual dates at the regular grid intervals, while for "days" (the default) shows the days since the beginning; if align.all.patients == TRUE, show.period is taken as "days".

period.in.days

The number of days at which the regular grid is drawn (or 0 for no grid).

show.legend

Logical, should the legend be drawn?

legend.x

The position of the legend on the x axis; can be "left", "right" (default), or a numeric value.

legend.y

The position of the legend on the y axis; can be "bottom" (default), "top", or a numeric value.

legend.bkg.opacity

A number between 0.0 and 1.0 specifying the opacity of the legend background.

legend.cex, legend.cex.title

The legend and legend title font sizes.

cex, cex.axis, cex.lab

numeric values specifying the cex of the various types of text.

show.cma

Logical, should the CMA type be shown in the title?

xlab

Named vector of x-axis labels to show for the two types of periods ("days" and "dates"), or a single value for both, or NULL for nothing.

ylab

Named vector of y-axis labels to show without and with CMA estimates, or a single value for both, or NULL for nonthing.

title

Named vector of titles to show for and without alignment, or a single value for both, or NULL for nonthing.

col.cats

A color or a function that specifies the single colour or the colour palette used to plot the different medication; by default rainbow, but we recommend, whenever possible, a colorblind-friendly palette such as viridis or colorblind_pal.

unspecified.category.label

A string giving the name of the unspecified (generic) medication category.

medication.groups.to.plot

the names of the medication groups to plot or NULL (the default) for all.

medication.groups.separator.show

a boolean, if TRUE (the default) visually mark the medication groups the belong to the same patient, using horizontal lines and alternating vertical lines.

medication.groups.separator.lty, medication.groups.separator.lwd, medication.groups.separator.color

graphical parameters (line type, line width and colour describing the visual marking og medication groups as beloning to the same patient.

medication.groups.allother.label

a string giving the label to use for the implicit __ALL_OTHERS__ medication group (defaults to "*").

lty.event, lwd.event, pch.start.event, pch.end.event

The style of the event (line style, width, and start and end symbols).

plot.events.vertically.displaced

Should consecutive events be plotted on separate rows (i.e., separated vertically, the default) or on the same row?

print.dose, cex.dose, print.dose.outline.col, print.dose.centered

Print daily dose as a number and, if so, how (color, size, position...).

plot.dose, lwd.event.max.dose, plot.dose.lwd.across.medication.classes

Show dose through the width of the event lines and, if so, what the maximum width should be, and should this maximum be by medication class or overall.

col.na

The colour used for missing event data.

col.continuation, lty.continuation, lwd.continuation

The color, style and width of the contuniation lines connecting consecutive events.

print.CMA

Logical, should the CMA values be printed?

CMA.cex

... and, if printed, what cex (numeric) to use?

plot.CMA

Logical, should the distribution of the CMA values across episodes/sliding windows be plotted? If TRUE (the default), the distribution is shown on the left-hand side of the plot, otherwise it is not.

plot.CMA.as.histogram

Logical, should the CMA plot be a histogram or a (truncated) density plot? Please note that it is TRUE by deafult for CMA_per_episode and FALSE for CMA_sliding_window, because usually there are more sliding windows than episodes. Also, the density estimate cannot be estimated for less than three different values.

plot.partial.CMAs.as

Should the partial CMAs be plotted? Possible values are "stacked", "overlapping" or "timeseries", or NULL for no partial CMA plots. Please note that plot.CMA and plot.partial.CMAs.as are independent of each other.

plot.partial.CMAs.as.stacked.col.bars, plot.partial.CMAs.as.stacked.col.border, plot.partial.CMAs.as.stacked.col.text

If plotting the partial CMAs as stacked bars, define their graphical attributes.

plot.partial.CMAs.as.timeseries.vspace, plot.partial.CMAs.as.timeseries.start.from.zero, plot.partial.CMAs.as.timeseries.col.dot, plot.partial.CMAs.as.timeseries.col.interval, plot.partial.CMAs.as.timeseries.col.text, plot.partial.CMAs.as.timeseries.interval.type, plot.partial.CMAs.as.timeseries.lwd.interval, plot.partial.CMAs.as.timeseries.alpha.interval, plot.partial.CMAs.as.timeseries.show.0perc, plot.partial.CMAs.as.timeseries.show.100perc

If plotting the partial CMAs as imeseries, these are their graphical attributes.

plot.partial.CMAs.as.overlapping.alternate, plot.partial.CMAs.as.overlapping.col.interval, plot.partial.CMAs.as.overlapping.col.text

If plotting the partial CMAs as overlapping segments, these are their graphical attributes.

CMA.plot.ratio

A number, the proportion of the total horizontal plot space to be allocated to the CMA plot.

CMA.plot.col, CMA.plot.border, CMA.plot.bkg, CMA.plot.text

Strings giving the colours of the various components of the CMA plot.

highlight.followup.window

Logical, should the follow-up window be plotted?

followup.window.col

The follow-up window colour.

highlight.observation.window

Logical, should the observation window be plotted?

observation.window.col, observation.window.opacity

Attributes of the observation window (colour, transparency).

alternating.bands.cols

The colors of the alternating vertical bands distinguishing the patients; can be NULL = don't draw the bandes; or a vector of colors.

bw.plot

Logical, should the plot use grayscale only (i.e., the gray.colors function)?

force.draw.text

Logical, if TRUE, always draw text even if too big or too small

min.plot.size.in.characters.horiz, min.plot.size.in.characters.vert

Numeric, the minimum size of the plotting surface in characters; horizontally (min.plot.size.in.characters.horiz) refers to the the whole duration of the events to plot; vertically (min.plot.size.in.characters.vert) refers to a single event. If the plotting is too small, possible solutions might be: if within RStudio, try to enlarge the "Plots" panel, or (also valid outside RStudio but not if using RStudio server start a new plotting device (e.g., using X11(), quartz() or windows(), depending on OS) or (works always) save to an image (e.g., jpeg(...); ...; dev.off()) and display it in a viewer.

max.patients.to.plot

Numeric, the maximum patients to attempt to plot.

export.formats

a string giving the formats to export the figure to (by default NULL, meaning no exporting); can be any combination of "svg" (just an SVG file), "html" (SVG + HTML + CSS + JavaScript, all embedded within one HTML document), "jpg", "png", "webp", "ps" or "pdf".

export.formats.fileprefix

a string giving the file name prefix for the exported formats (defaults to "AdhereR-plot").

export.formats.height, export.formats.width

numbers giving the desired dimensions (in pixels) for the exported figure (defaults to sane values if NA).

export.formats.save.svg.placeholder

a logical, if TRUE, save an image placeholder of type given by export.formats.svg.placeholder.type for the SVG image.

export.formats.svg.placeholder.type

a string, giving the type of placeholder for the SVG image to save; can be "jpg", "png" (the default) or "webp".

export.formats.svg.placeholder.embed

a logical, if TRUE, embed the placeholder image in the HTML document (if any) using base64 encoding, otherwise (the default) leave it as an external image file (works only when an HTML document is exported and only for JPEG or PNG images.

export.formats.html.template, export.formats.html.javascript, export.formats.html.css

character strings or NULL (the default) giving the path to the HTML, JavaScript and CSS templates, respectively, to be used when generating the HTML+CSS semi-interactive plots; when NULL, the default ones included with the package will be used. If you decide to define new templates please use the default ones for inspiration and note that future version are not guaranteed to be backwards compatible!

export.formats.directory

a string; if exporting, which directory to export to; if NA (the default), creates the files in a temporary directory.

generate.R.plot

a logical, if TRUE (the default), generate the standard (base R) plot for plotting within R.

suppress.warnings

Logical, if TRUE don't show any warnings.

...

other parameters (to be passed to the estimation and plotting of the simple CMA)

Details

The x-axis represents time (either in days since the earliest date or as actual dates), with consecutive events represented as ascending on the y-axis.

Each event is represented as a segment with style lty.event and line width lwd.event starting with a pch.start.event and ending with a pch.end.event character, coloured with a unique color as given by col.cats, extending from its start date until its end date. Consecutive events are thus represented on consecutive levels of the y-axis and are connected by a "continuation" line with col.continuation colour, lty.continuation style and lwd.continuation width; these continuation lines are purely visual guides helping to perceive the sequence of events, and carry no information about the avilability of medicine in this interval.

Above these, the treatment episodes or the sliding windows are represented in a stacked manner from the earlieast (left, bottom of the stack) to the latest (right, top of the stack), each showing the CMA as percent fill (capped at 100% even if CMA values may be higher) and also as text.

The follow-up and the observation windows are plotted as empty an rectangle and as shaded rectangle, respectively (for some CMAs the observation window might be adjusted in which case the adjustment may also be plotted using a different shading).

The kernel density ("smoothed histogram") of the CMA estimates across treatment episodes/sliding windows (if more than 2) can be visually represented as well in the left side of the figure (NB, their horizontal scales may be different across patients).

When several patients are displayed on the same plot, they are organized vertically, and alternating bands (white and gray) help distinguish consecutive patients. Implicitely, all patients contained in the cma object will be plotted, but the patients.to.plot parameter allows the selection of a subset of patients.

Finally, the y-axis shows the patient ID and possibly the CMA estimate as well.

Any not explicitely defined arguments are passed to the simple CMA estimation and plotting function; therefore, for more info about possible estimation parameters plese see the help for the appropriate simple CMA, and for possible aesthetic tweaks, please see the help for their plotting.

See Also

See the simple CMA estimation CMA1 to CMA9 and plotting plot.CMA1 functions for extra parameters.

Examples

## Not run: 
cmaW <- CMA_sliding_window(CMA=CMA1,
                        data=med.events,
                        ID.colname="PATIENT_ID",
                        event.date.colname="DATE",
                        event.duration.colname="DURATION",
                        event.daily.dose.colname="PERDAY",
                        medication.class.colname="CATEGORY",
                        carry.only.for.same.medication=FALSE,
                        consider.dosage.change=FALSE,
                        followup.window.start=0,
                        observation.window.start=0,
                        observation.window.duration=365,
                        sliding.window.start=0,
                        sliding.window.start.unit="days",
                        sliding.window.duration=90,
                        sliding.window.duration.unit="days",
                        sliding.window.step.duration=7,
                        sliding.window.step.unit="days",
                        sliding.window.no.steps=NA,
                        date.format="%m/%d/%Y"
                       );
plot(cmaW, patients.to.plot=c("1","2"));
cmaE <- CMA_per_episode(CMA=CMA1,
                        data=med.events,
                        ID.colname="PATIENT_ID",
                        event.date.colname="DATE",
                        event.duration.colname="DURATION",
                        event.daily.dose.colname="PERDAY",
                        medication.class.colname="CATEGORY",
                        carry.only.for.same.medication=FALSE,
                        consider.dosage.change=FALSE,
                        followup.window.start=0,
                        observation.window.start=0,
                        observation.window.duration=365,
                        date.format="%m/%d/%Y"
                       );
plot(cmaE, patients.to.plot=c("1","2"));
## End(Not run)

[Package AdhereR version 0.7.0 Index]