Draw an interactive forest plot for a meta-analysis

Draws the forest plot of a fitted meta-analysis, with the data behind every study a hover and a click away. Hovering over a study shows its effect, weight and the columns named in hover; clicking it opens its full record, every column of data, under the plot. Hovering over the pooled diamond shows the heterogeneity statistics and the prediction interval. Risk of bias judgments, given in rob, are drawn as traffic lights beside each study.

Usage

ggmeta(
  x,
  data = NULL,
  columns = NULL,
  rob = NULL,
  hover = NULL,
  cumulative = FALSE,
  exponentiate = NULL,
  xlim = NULL,
  favors = NULL,
  xlab = NULL,
  title = NULL,
  caption = NULL,
  family = "Lato"
)

Arguments

x: A fitted meta-analysis: an rma.uni object from metafor::rma(), or a meta object from the 'meta' package, such as the result of meta::metabin() or meta::metagen(). Models with moderators are not supported.
data: Optional data frame with one row per study, in the order of the model, holding the columns to show. Defaults to the data stored in the fit, which is there when the model was fitted with a data argument.
columns: Names of columns of data to print as text columns beside the study labels, such as event counts. Name the vector to set the column headers.
rob: Names of columns of data holding risk of bias judgments, one per domain, drawn as traffic lights. Name the vector to set the column headers, such as c(D1 = "rob.R", Overall = "rob.overall"). Judgments are matched by their wording: "low", "some concerns" or "moderate", "unclear", "high" or "serious", "critical", and "no information", in any case.
hover: Names of columns of data shown in each study's hover card. Defaults to columns.
cumulative: Show the cumulative meta-analysis rather than the individual studies.
exponentiate: Show effects on the ratio scale. Defaults to TRUE for ratio measures (RR, OR, HR, IRR, ROM and Peto odds ratios), which are modeled on the log scale.
xlim: Optional limits of the effect axis, on the scale shown.
favors: Optional labels for the two sides of the null line, such as c("Favors treatment", "Favors control").
xlab: Axis label. Defaults to the name of the effect measure.
title, caption: Title above the plot and note below it.
family: Font family. The package ships Lato and registers it on load.

Value

An object of class ggmeta, which prints as an interactive widget. Use graph_widget(), graph_plot() or graph_save() for the widget, a static ggplot or a file, and animate_meta() for the cumulative replay.

Details

Square area follows the study's weight in the model. The diamond is the pooled estimate with its confidence interval, and the line through it the prediction interval for a random effects model. Ratio measures such as risk, odds and hazard ratios are shown on a log axis. A confidence interval that runs past the axis ends in an arrow.

With cumulative = TRUE, each row shows the pooled estimate from the studies up to and including it, in the order of the data, so sort the data by year before fitting the model for a cumulative meta-analysis over time. animate_meta() replays that sequence as an animation.

Examples

if (requireNamespace("metafor", quietly = TRUE)) {
  dat <- metafor::escalc(
    measure = "OR", ai = p2y12.mi, n1i = p2y12.total,
    ci = aspirin.mi, n2i = aspirin.total,
    data = metadat::dat.chiarito2020, slab = paste(study, year)
  )
  dat <- dat[!is.na(dat$yi), ]
  dat$p2y12 <- paste0(dat$p2y12.mi, "/", dat$p2y12.total)
  dat$aspirin <- paste0(dat$aspirin.mi, "/", dat$aspirin.total)
  fit <- metafor::rma(yi, vi, data = dat)

  ggmeta(
    fit,
    columns = c("P2Y12 inhibitor" = "p2y12", Aspirin = "aspirin"),
    rob = c(R = "rob.R", D = "rob.D", Mi = "rob.Mi", Me = "rob.Me",
            S = "rob.S", Overall = "rob.overall"),
    favors = c("Favors P2Y12 inhibitor", "Favors aspirin")
  )
}