Confidence interval lines in forest plots

When making a forest plot, if a confidence interval line is narrower than the point representing the estimate we may wish to plot the line differently. In this package, this is possible by using the panel.width argument in the forest_plot() function.

The sections below show how to change the colour of confidence lines and/or plot confidence lines before or after points. After using these methods, you should still carefully check the output (i.e. your final output file, not an RStudio preview) to ensure confidence interval lines are not hidden.

Changing the colour

To plot narrow confidence widths a different colour, set the panel.width argument of forest_plot() (this will also fix the width of each panel).

Notes: This has been designed to work well for shape 15 (the default) and 22. The calculation of sizes (and accounting for the stroke aesthetic) may not be entirely accurate, so check the output and change the plot.width argument as needed. Confidence intervals are assumed to be centred on the point estimate.

resultsA <- dplyr::filter(ckbplotr_forest_data, name == "A")
resultsB <- dplyr::filter(ckbplotr_forest_data, name == "B")

forest_plot(
  panels            = list(resultsA, resultsB),
  col.key           = "variable",
  row.labels        = ckbplotr_row_labels,
  row.labels.levels = c("heading", "subheading", "label"),
  rows              = c("Lipoprotein particle concentration"),
  exponentiate      = TRUE,
  panel.names       = c("Analysis A", "Analysis B"),
  ci.delim          = " - ",
  xlim              = c(0.9, 1.1),
  xticks            = c(0.9, 1, 1.1),
  blankrows         = c(1, 1, 0, 1),
  scalepoints       = TRUE,
  pointsize         = 8,
  col.left          = c("n"),
  col.left.heading  = c("No. of\nevents"),
  col.heading.space = 0,
  
  # set panel width
  panel.width       = unit(18, "mm"))

The cicolour argument can be a character vector - the last element will be used for narrow confidence intervals. It can be a vector of all names of colours, or all names of columns (which contain colour names).

Plotting lines under or over points

As well as changing colour, we may also wish to change if confidence interval lines are plotted under or over the point estimates. This can be done using the panel.width argument.

forest_plot(
  panels            = list(resultsA, resultsB),
  col.key           = "variable",
  row.labels        = ckbplotr_row_labels,
  row.labels.levels = c("heading", "subheading", "label"),
  rows              = c("Lipoprotein particle concentration"),
  exponentiate      = TRUE,
  panel.names       = c("Analysis A", "Analysis B"),
  ci.delim          = " - ",
  xlim              = c(0.9, 1.1),
  xticks            = c(0.9, 1, 1.1),
  blankrows         = c(1, 1, 0, 1),
  scalepoints       = TRUE,
  pointsize         = 8,
  col.left          = c("n"),
  col.left.heading  = c("No. of\nevents"),
  
  # set panel width + CI under or over
  panel.width       = unit(18, "mm"),
  shape             = 22,
  stroke            = 0.5,
  fill              = "white")

Changing colour and plotting of lines

When using panel.width, cicolour can be a list of vectors of colour names. fill can also be list of colour names.

resultsA <- dplyr::filter(ckbplotr_forest_data, name == "A")
resultsB <- dplyr::filter(ckbplotr_forest_data, name == "B")

forest_plot(
  panels            = list(resultsA, resultsB),
  col.key           = "variable",
  row.labels        = ckbplotr_row_labels,
  row.labels.levels = c("heading", "subheading", "label"),
  rows              = c("Lipoprotein particle concentration"),
  exponentiate      = TRUE,
  panel.names       = c("Analysis A", "Analysis B"),
  ci.delim          = " - ",
  xlim              = c(0.9, 1.1),
  xticks            = c(0.9, 1, 1.1),
  blankrows         = c(1, 1, 0, 1),
  scalepoints       = TRUE,
  pointsize         = 8,
  col.left          = c("n"),
  col.left.heading  = c("No. of\nevents"),
  
  # set panel width + CI and fill colours
  panel.width       = unit(18, "mm"),
  stroke            = 0.5,
  shape             = 22,
  fill              = list("black",
                           "white"),
  cicolour          = list(c("black", "white"),
                           c("black", "black"))
  )