Draw a Baujat plot to explore heterogeneity in meta-analysis.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
baujat(x, ...)
## S3 method for class 'meta'
baujat(x,
yscale=1, xlim, ylim,
xlab="Contribution to overall heterogeneity",
ylab="Influence on overall result",
pch=21, cex=1, col="black", bg="darkgray",
studlab=TRUE, cex.studlab=0.8,
xmin=0, ymin=0, pos=2, offset=0.5,
grid=TRUE, col.grid="lightgray", lty.grid="dotted", lwd.grid=par("lwd"),
pty="s", ...)
``` |

`x` |
An object of class |

`yscale` |
Scaling factor for values on y-axis. |

`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. |

`pch` |
The plotting symbol used for individual studies. |

`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 |

`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 |

`cex.studlab` |
The magnification for study labels. |

`xmin` |
A numeric specifying minimal value to print study labels (on x-axis). |

`ymin` |
A numeric specifying minimal value to print study labels (on y-axis). |

`pos` |
A position specifier for study labels (see |

`offset` |
Offset for study labels (see |

`grid` |
A logical indicating whether a grid is printed in the plot. |

`col.grid` |
Colour for grid lines. |

`lty.grid` |
The line type for grid lines. |

`lwd.grid` |
The line width for grid lines. |

`pty` |
A character specifying type of plot region (see |

`...` |
Graphical arguments as in |

Baujat et al. (2002) introduced a scatter plot to explore
heterogeneity in meta-analysis. On the x-axis the contribution of
each study to the overall heterogeneity statistic (see list object
`Q`

of the meta-analysis object `x`

) is plotted. On the
y-axis the standardised difference of the overall treatment effect
with and without each study is plotted; this quantity describes the
influence of each study on the overal treatment effect.

Internally, the `metainf`

function is used to calculate
the values on the y-axis.

A data.frame with the following variables:

`x` |
Coordinate on x-axis (contribution to heterogeneity statistic). |

`y` |
Coordinate on y-axis (influence on overall treatment effect). |

Guido Schwarzer sc@imbi.uni-freiburg.de

Baujat B, Mahé C, Pignon JP, Hill C (2002),
A graphical method for exploring heterogeneity in meta-analyses:
Application to a meta-analysis of 65 trials.
*Statistics in Medicine*, **30**, 2641–2652.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
data(Olkin95)
m1 <- metabin(event.e, n.e, event.c, n.c, data=Olkin95,
studlab=author, sm="OR", method="I")
# Generate Baujat plot
baujat(m1)
# Do not print study labels if the x-value is smaller than 4 and the
# y-value is smaller than 1.
baujat(m1, yscale=10, xmin=4, ymin=1)
# Change position of study labels
baujat(m1, yscale=10, xmin=4, ymin=1,
pos=1, xlim=c(0, 6.5))
# Generate Baujat plot and assign x- and y- coordinates to R object b1
b1 <- baujat(m1)
# Calculate overall heterogeneity statistic
sum(b1$x)
m1$Q
``` |

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