errorbarClinData: Interactive plot of confidence interval/error interval of...
In clinDataReview: Clinical Data Review Tool

errorbarClinData

R Documentation

Interactive plot of confidence interval/error interval of clinical data.

Description

This plot is designed to display summary statistics of a continuous variable with (confidence) intervals.
The intervals are either displayed:

vertically if yErrorVar is specified
horizontally if xErrorVar is specified

Error bars can visualized by group, via the color variable parameter.
Different symbols are set for each central point of the error bar via the shape variable parameter.

Usage

errorbarClinData(
  data,
  xVar,
  xLab = getLabelVar(xVar, labelVars = labelVars),
  yVar,
  yLab = getLabelVar(yVar, labelVars = labelVars),
  yErrorVar = NULL,
  yErrorLab = getLabelVar(yErrorVar, labelVars = labelVars),
  xErrorVar = NULL,
  xErrorLab = getLabelVar(xErrorVar, labelVars = labelVars),
  xLabVars = NULL,
  xAxisLab = paste(c(xLab, xErrorLab), collapse = " and "),
  yAxisLab = paste(c(yLab, yErrorLab), collapse = " and "),
  colorVar = NULL,
  colorLab = getLabelVar(colorVar, labelVars = labelVars),
  colorPalette = NULL,
  shapeVar = NULL,
  shapeLab = getLabelVar(shapeVar, labelVars = labelVars),
  shapePalette = NULL,
  size = 6,
  titleExtra = NULL,
  title = paste(c(paste(yAxisLab, "vs", xAxisLab), titleExtra), collapse = "<br>"),
  subtitle = NULL,
  caption = NULL,
  labelVars = NULL,
  mode = "markers",
  legendPosition = "bottom",
  width = NULL,
  height = NULL,
  pathVar = NULL,
  pathLab = getLabelVar(pathVar, labelVars = labelVars),
  hoverVars,
  hoverLab,
  id = paste0("plotClinData", sample.int(n = 1000, size = 1)),
  selectVars = NULL,
  selectLab = getLabelVar(selectVars, labelVars = labelVars),
  table = FALSE,
  tableVars,
  tableLab,
  tableButton = TRUE,
  tablePars = list(),
  verbose = FALSE
)

Arguments

`data`	Data.frame with data.
`xVar`	String with column of `data` containing x-variable.
`xLab`	String with label for `xVar`.
`yVar`	String with column of `data` containing y-variable.
`yLab`	String with label for `xVar`.
`xErrorVar, yErrorVar`	String with variable of `data` containing the width of the interval (from the center of the interval) for horizontal or vertical intervals.
`xErrorLab, yErrorLab`	String with labels for `xErrorVar`/`yErrorVar` variables.
`xLabVars`	(vertical error bars) Character vector with variable(s) to be displayed as the labels of the ticks in the x-axis. By default, `xVar` is displayed. In case the variable(s) contain different elements by `xVar`, they are combined and displayed below each other.
`xAxisLab, yAxisLab`	Label for the x/y-axis.
`colorVar`	(optional) String with color variable.
`colorLab`	String with label for `colorVar`.
`colorPalette`	(optional) Named character vector with color palette. If not specified, the viridis color palette is used. See `clinColors`.
`shapeVar`	(optional) String with shape variable.
`shapeLab`	String with label for `shapeVar`.
`shapePalette`	(optional) Named character vector with shape palette, `clinShapes` by default.
`size`	Integer with size of markers in pixels, 6 by default.
`titleExtra`	String with extra title for the plot (appended after `title`).
`title`	String with title for the plot.
`subtitle`	String with subtitle. The subtitle is included at the top left of the plot, below the title.
`caption`	String with caption. The caption is included at the bottom right of the plot. Please note that this might overlap with vertical or rotated x-axis labels.
`labelVars`	Named character vector containing variable labels.
`mode`	String with the mode of the plot, 'markers' by default, so only data points are displayed. This can also be set to 'lines' to include a line connecting the center of the error bars instead; or 'lines+markers' to include both a marker and a line. See `mode` attribute for plotly scatter.
`legendPosition`	String with position of the legend, among: 'top'/'left'/'bottom'/'right', 'bottom' by default.
`width`	Numeric, width of the plot in pixels, 700 by default.
`height`	Numeric, height of the plot in pixels, 700 by default.
`pathVar`	String with variable of `data` containing hyperlinks with path to the subject-specific report, formatted as: <a href="./path-to-report">label</a> . If multiple, they should be separated by: ', '. The report(s) will be: compressed to a zip file and downloaded if the user clicks on the 'p' (a.k.a 'profile') key when hovering on a point of the plot included in a collapsible row, and clickable with hyperlinks in the table
`pathLab`	String with label for `pathVar`, included in the collapsible row in the table.
`hoverVars`	Character vector with variable(s) to be displayed in the hover, by default any position and aesthetic variables displayed in the plot.
`hoverLab`	Named character vector with labels for `hoverVars`.
`id`	String with general id for the plot: 'id' is used as `group` for the `SharedData` 'button:[id]' is used as button ID if `table` is TRUE If not specified, a random id, as 'plotClinData[X]' is used.
`selectVars`	(optional) Character vector with variable(s) from `data` for which a selection box should be included. This enables to select the data displayed in the plot (and associated table).
`selectLab`	(Named) character vector with label for `selectVars`.
`table`	Logical, if TRUE (FALSE by default) returns also a `datatable` containing the plot data. (The plot and the table are not linked.)
`tableVars`	Character vector with variables to be included in the table.
`tableLab`	Named character vector with labels for each `tableVars`.
`tableButton`	Logical, if TRUE (by default) the table is included within an HTML button.
`tablePars`	List with parameters passed to the `getClinDT` function.
`verbose`	Logical, if TRUE (FALSE by default) progress messages are printed in the current console. For the visualizations, progress messages during download of subject-specific report are displayed in the browser console.

Value

Either:

if a table is requested: a clinDataReview object, a.k.a a list with the 'plot' (plotly object) and 'table' (datatable object)
otherwise: a plotly object

Author(s)

Laure Cougnaud

Examples

library(clinUtils)

data(dataADaMCDISCP01)
labelVars <- attr(dataADaMCDISCP01, "labelVars")

## Summary plot with vertical error bars

dataVSDIABP <- subset(dataADaMCDISCP01$ADVS, 
	PARAMCD == "DIABP" & ANL01FL == "Y" &
	AVISIT %in% c("Baseline", "Week 2", "Week 4", "Week 6", "Week 8")
)

# compute summary statistics by visit
if (requireNamespace("inTextSummaryTable", quietly = TRUE)) {
	
summaryTableVSDIABP <- inTextSummaryTable::computeSummaryStatisticsTable(
	data = dataVSDIABP,
	rowVar = c("AVISIT", "ATPT"),
	var = "AVAL",
	stats = inTextSummaryTable::getStats(c("n", "Mean", "SE")),
	labelVars = labelVars
)
dataPlot <- subset(summaryTableVSDIABP, !isTotal)

errorbarClinData(
	data = dataPlot,
	xVar = "AVISIT",
	colorVar = "ATPT",
	# use non-rounded statistics for the plot
	yVar = "statMean", yErrorVar = "statSE", 
	yLab = "Mean", yErrorLab = "Standard Error",
	# include lines connecting the error bars
	mode = "markers+lines",
	labelVars = labelVars
)

# add number of subjects in labels
dataPlot$nSubj <- with(dataPlot, paste0("N=", n))
errorbarClinData(
	data = dataPlot,
	xVar = "AVISIT", 
	xLabVars = c("AVISIT", "nSubj"),
	colorVar = "ATPT",
	yVar = "statMean", yLab = "Mean",
	yErrorVar = "statSE", yErrorLab = "Standard error",
	mode = "markers+lines",
	title = paste("Diastolic Blood Pressure summary profile by actual visit",
		"and analysis timepoint"),
	labelVars = labelVars
)

## Add a selection box
if(interactive()){
  summaryTable <- inTextSummaryTable::computeSummaryStatisticsTable(
    data = subset(dataADaMCDISCP01$ADVS, 
      ANL01FL == "Y" &
      AVISIT %in% c("Baseline", "Week 2", "Week 4", "Week 6", "Week 8")
    ),
    rowVar = c("PARAM", "AVISIT", "ATPT"),
    var = "AVAL",
    stats = inTextSummaryTable::getStats(c("Mean", "SE")),
    labelVars = labelVars
  )
  dataPlot <- subset(summaryTable, !isTotal)
  errorbarClinData(
    data = dataPlot,
    xVar = "AVISIT", 
    colorVar = "ATPT",
    yVar = "statMean", yLab = "Mean",
    yErrorVar = "statSE", yErrorLab = "Standard error",
    mode = "markers+lines",
    title = paste("Lab parameters summary profile by actual visit",
      "and analysis timepoint"),
    labelVars = labelVars,
    selectVars = "PARAM"
  )
}

## Summary plot with horizontal error bars

# Data of interest: ratio from baseline at week 16
dataLBW8 <- subset(dataADaMCDISCP01$ADLBC, grepl("Week 8", AVISIT))
# compute ratio from baseline
dataLBW8$R2BASE <- with(dataLBW8, AVAL/BASE) 
dataLBW8 <- subset(dataLBW8, !is.na(R2BASE))
# Order actual treatments
dataLBW8$TRTA <- with(dataLBW8, reorder(TRTA, TRTAN))

# compute summary statistics of the ratio per baseline per parameter
summaryTableLBW8 <- inTextSummaryTable::computeSummaryStatisticsTable(
	data = dataLBW8,
	var = "R2BASE",
	rowVar = "PARAM",
	colVar = "TRTA",
	stats = inTextSummaryTable::getStats(x = dataLBW8$R2BASE, type = c("n", "Median", "SD"))
)
dataPlot <- subset(summaryTableLBW8, !isTotal)
# extract direction of ratio
dataPlot$dir <- factor(
	ifelse(dataPlot$statMedian >= 1, "Increase", "Decrease"),
	levels = c("Decrease", "Increase")
)
# compute relative ratio (percentage above 1)
dataPlot$statMedianRelative <- with(dataPlot,
	ifelse(statMedian < 1, 1/statMedian, statMedian)
)
# order based on mean relative ratio across treatment arms
params <- names(sort(with(dataPlot, tapply(statMedianRelative, PARAM, mean))))
dataPlot$PARAM <- factor(dataPlot$PARAM, levels = params)
errorbarClinData(
	data = dataPlot,
	xVar = "statMedianRelative", xErrorVar = "statSD",
	xLab = "Median", xErrorLab = "Standard deviation",
	xAxisLab = "Relative ratio from baseline (Median +- SD)",
	yVar = "PARAM",
	colorVar = "TRTA",
	shapeVar = "dir", shapeLab = "Direction of ratio",
	shapePalette = c(`Decrease` = 25, `Increase` = 24),
	size = 10,
	labelVars = labelVars,
	title = "Summary ratio from baseline at week 8 by treatment"
)

}

clinDataReview documentation built on March 7, 2023, 5:13 p.m.