Description Usage Arguments Details Value References Examples

`plotMetaAnalysisForest`

performs a meta-analysis and creates a forest plot of effect size estimates.

1 2 3 4 5 6 7 8 9 10 | ```
plotMetaAnalysisForest(
logRr,
logLb95Ci,
logUb95Ci,
labels,
xLabel = "Relative risk",
limits = c(0.1, 10),
hakn = FALSE,
fileName = NULL
)
``` |

`logRr` |
A numeric vector of effect estimates on the log scale. |

`logLb95Ci` |
The lower bound of the 95 percent confidence interval on the log scale. |

`logUb95Ci` |
The upper bound of the 95 percent confidence interval on the log scale. |

`labels` |
A vector containing the labels for the various estimates. |

`xLabel` |
The label on the x-axis: the name of the effect estimate. |

`limits` |
The limits of the effect size axis. |

`hakn` |
A logical indicating whether method by Hartung and Knapp should be used to adjust test statistics and confidence intervals. |

`fileName` |
Name of the file where the plot should be saved, for example 'plot.png'. See the
function |

Creates a forest plot of effect size estimates, and includes a meta-analysis estimate using a random effects model. The DerSimonian-Laird estimate (1986) is used.

A Ggplot object. Use the `ggsave`

function to save to file.

DerSimonian R, Laird N (1986), Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177-188.

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