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labbe

L'Abbé plot for meta-analysis with binary outcomes

Description

Draw a L'Abbé plot for meta-analysis with binary outcomes.

Usage

## S3 method for class 'metabin'
labbe(
  x,
  xlim,
  ylim,
  xlab = NULL,
  ylab = NULL,
  TE.fixed = x$TE.fixed,
  TE.random = x$TE.random,
  comb.fixed = x$comb.fixed,
  comb.random = x$comb.random,
  backtransf = x$backtransf,
  axes = TRUE,
  pch = 21,
  text = NULL,
  cex = 1,
  col = "black",
  bg = "lightgray",
  lwd = 1,
  lwd.fixed = lwd,
  lwd.random = lwd,
  lty.fixed = 2,
  lty.random = 9,
  col.fixed = col,
  col.random = col,
  nulleffect = TRUE,
  lwd.nulleffect = lwd,
  col.nulleffect = "lightgray",
  sm = x$sm,
  weight,
  studlab = FALSE,
  cex.studlab = 0.8,
  pos.studlab = 2,
  label.e = x$label.e,
  label.c = x$label.c,
  ...
)

## Default S3 method:
labbe(
  x,
  y,
  xlim,
  ylim,
  xlab = NULL,
  ylab = NULL,
  TE.fixed = NULL,
  TE.random = NULL,
  comb.fixed = !is.null(TE.fixed),
  comb.random = !is.null(TE.random),
  backtransf = TRUE,
  axes = TRUE,
  pch = 21,
  text = NULL,
  cex = 1,
  col = "black",
  bg = "lightgray",
  lwd = 1,
  lwd.fixed = lwd,
  lwd.random = lwd,
  lty.fixed = 2,
  lty.random = 9,
  col.fixed = col,
  col.random = col,
  nulleffect = TRUE,
  lwd.nulleffect = lwd,
  col.nulleffect = "lightgray",
  sm = "",
  weight,
  studlab = FALSE,
  cex.studlab = 0.8,
  pos.studlab = 2,
  label.e = NULL,
  label.c = NULL,
  ...
)

Arguments

`x`	An object of class `metabin`. Alternatively, the x coordinates of points of the L'Abbé plot.
`xlim`	The x limits (min, max) of the plot.
`ylim`	The y limits (min, max) of the plot.
`xlab`	A label for the x-axis.
`ylab`	A label for the y-axis.
`TE.fixed`	A numeric or vector specifying combined fixed effect estimate(s).
`TE.random`	A numeric or vector specifying combined random effects estimate(s).
`comb.fixed`	A logical indicating whether the pooled fixed effect estimate should be plotted.
`comb.random`	A logical indicating whether the pooled random effects estimate should be plotted.
`backtransf`	A logical indicating which values should be printed on x- and y-axis (see Details).
`axes`	A logical indicating whether axes should be drawn on the plot.
`pch`	The plotting symbol used for individual studies.
`text`	A character vector specifying the text to be used instead of plotting symbol.
`cex`	The magnification to be used for plotting symbol.
`col`	A vector with colour of plotting symbols.
`bg`	A vector with background colour of plotting symbols (only used if `pch` in `21:25`).
`lwd`	The line width.
`lwd.fixed`	The line width(s) for fixed effect estimate(s) (if `comb.fixed` is not `NULL` or `FALSE`).
`lwd.random`	The line width(s) for random effects estimate(s) (if `comb.random` is not `NULL` or `FALSE`).
`lty.fixed`	Line type(s) for fixed effect estimate(s).
`lty.random`	Line type(s) for random effects estimate(s).
`col.fixed`	Colour of line(s) for fixed effect estimate(s).
`col.random`	Colour of line(s) for random effects estimate(s).
`nulleffect`	A logical indicating whether line for null effect should be added to the plot..
`lwd.nulleffect`	Width of line for null effect.
`col.nulleffect`	Colour of line for null effect.
`sm`	A character string indicating underlying summary measure, i.e., `"RD"`, `"RR"`, `"OR"`, or `"ASD"`.
`weight`	Either a numeric vector specifying relative sizes of plotting symbols or a character string indicating which type of plotting symbols is to be used for individual treatment estimates. One of missing (see Details), `"same"`, `"fixed"`, or `"random"`, can be abbreviated. Plot symbols have the same size for all studies or represent study weights from fixed effect or random effects model.
`studlab`	A logical indicating whether study labels should be printed in the graph. A vector with study labels can also be provided (must be of same length as `x$event.e` then).
`cex.studlab`	Size of study labels.
`pos.studlab`	Position of study labels, see argument `pos` in `text`.
`label.e`	Label for experimental group.
`label.c`	Label for control group.
`...`	Graphical arguments as in `par` may also be passed as arguments.
`y`	The y coordinates of the L'Abbé plot, if argument `x` is not an object of class `metabin`.

Details

A L'Abbé plot is a scatter plot with the risk in the control group on the x-axis and the risk in the experimental group on the y-axis (L'Abbé et al., 1987). It can be used to evaluate heterogeneity in meta-analysis. Furthermore, this plot can aid to choose a summary measure (odds ratio, risk ratio, risk difference) that will result in more consistent results (Jiménez et al., 1997; Deeks, 2002).

If argument backtransf is TRUE (default), event probabilities will be printed on x- and y-axis. Otherwise, transformed event probabilities will be printed as defined by the summary measure, i.e., log odds of probabilities for odds ratio as summary measure (sm = "OR"), log probabilities for sm = "RR", and arcsine-transformed probabilities for sm = "ASD".

If comb.fixed is TRUE, the pooled estimate of the fixed effect model is plotted as a line. If comb.random is TRUE, the pooled estimate of the random effects model is plotted as a line.

Information from object x is utilised if argument weight is missing. Weights from the fixed effect model are used (weight = "fixed") if argument x$comb.fixed is TRUE; weights from the random effects model are used (weight = "random") if argument x$comb.random is TRUE and x$comb.fixed is FALSE.

Author(s)

Guido Schwarzer sc@imbi.uni-freiburg.de

References

Deeks JJ (2002): Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Statistics in Medicine, 21, 1575–600

Jiménez FJ, Guallar E, Martín-Moreno JM (1997): A graphical display useful for meta-analysis. European Journal of Public Health, 1, 101–5

L'Abbé KA, Detsky AS, O'Rourke K (1987): Meta-analysis in clinical research. Annals of Internal Medicine, 107, 224–33

Examples

data(Olkin1995)
m1 <- metabin(ev.exp, n.exp, ev.cont, n.cont,
              data = Olkin1995,
              studlab = paste(author, year),
              sm = "RR", method = "I")

# L'Abbe plot for risk ratio
#
labbe(m1)

# L'Abbe plot for odds ratio
#
labbe(m1, sm = "OR")
# same plot
labbe(update(m1, sm = "OR"))

# L'Abbe plot for risk difference
#
labbe(m1, sm = "RD")

# L'Abbe plot on log odds scale
#
labbe(m1, sm = "OR", backtransf = FALSE)

# L'Abbe plot for odds ratio with coloured lines for various
# treatment effects (defined as log odds ratios)
#
mycols <- c("blue", "yellow", "green", "red",
            "green", "yellow", "blue")
labbe(m1, sm = "OR",
      comb.random = FALSE,
      TE.fixed = log(c(1 / 10, 1 / 5, 1 / 2, 1, 2, 5, 10)),
      col.fixed = mycols, lwd.fixed = 2)

# L'Abbe plot on log odds scale with coloured lines for various
# treatment effects (defined as log odds ratios)
#
labbe(m1, sm = "OR",
      comb.random = FALSE,
      TE.fixed = log(c(1 / 10, 1 / 5, 1 / 2, 1, 2, 5, 10)),
      col.fixed = mycols, lwd.fixed = 2,
      backtransf = FALSE)