Description Usage Arguments Value

Compute meta-analysis weights and corresponding pooled estimates given a set of estimates and standard errors. Weights are simply defined by the inverse variance, where the variance is the sum of the study-specific and random effects variance.

1 |

`dat` |
Meta-analysis data. This should be a data frame with three columns, called "name", "est" and "se" giving the study name, study-specific parameter estimates and corresponding standard errors respectively. Numeric or character study names are permitted. If the data frame has more than three columns, the first three are used. If the first three columns are called "name", "est" and "se" in some order, they are re-ordered appropriately, otherwise they are re-named. |

`resd` |
Random effects standard deviation. Set |

`egger` |
Set to |

A list with the following components:

`est` |
Original study-specific estimates (if |

`pool` |
Pooled estimate |

`poolse` |
Pooled standard error |

`poolci` |
Pooled 95% confidence interval |

`pwtfe` |
Weights for fixed effects model, normalised to sum to 1 |

`pwtre` |
Weights for desired random effects standard deviation, normalised to sum to 1 |

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