Description Usage Arguments Details Author(s) See Also Examples

This package conducts fixed-effects (with inverse variance weighting) and random-effects [DerSimonian and Laird (1986)] meta-analyses of case-control or family-based (TDT) genetic data. In addition, catmap performs meta-analyses which combine these two types of study designs. Specifically, this package implements a fixed-effects model [Kazeem and Farrall (2005)] and a random-effects model [Nicodemus (2008)] for combined studies.

1 |

`dataset` |
A |

`ci` |
A numeric value. The confidence level for confidence intervals; 0 < ci < 1. |

`printout` |
A boolean. Toggles whether a text file of the models and Q statistic results should get saved to the working directory. |

Use the output of the `catmap`

function to generate figures using
secondary functions. These secondary functions produce output as either
a txt file, a pdf plot, or both.

A standard forest plot is available via `catmap.forest`

.
A funnel plot is available via `catmap.funnel`

. However,
no formal test of publication bias is available (see
[Ioannidis and Trikalinos (2007)]).

In addition, cumulative meta-analyses over time (`catmap.cumulative`

)
and leave-one-out sensitivity analyses (`catmap.sense`

) are
available for the fixed-effects estimates and random-effects estimates.

Algorithm designed and implemented by Kristin K. Nicodemus. Code modified and updated by Thom Quinn.

`catmap`

, `catmap.forest`

,
`catmap.sense`

, `catmap.cumulative`

,
`catmap.funnel`

1 2 | ```
data(catmapdata)
catmapobject <- catmap(catmapdata, 0.95, TRUE)
``` |

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