catmap {catmap}

catmap: Case-Control and TDT Meta-Analysis Package

Description

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.

Usage

catmap(dataset, ci = 0.95, printout = FALSE)

Arguments

dataset

A data.frame, matrix, or file location. The input should have the following column names: name, study, t, nt, caserisk, controlrisk, casenotrisk, controlnotrisk. For a file location, provide the data in a tab-delimited format. Note that the header must have these exact columns and all cells in the table must have an entry, even if the entry is 0 or NA. See catmapdata for an example.

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.

Details

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.

Author(s)

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

See Also

catmap, catmap.forest, catmap.sense, catmap.cumulative, catmap.funnel

Examples

data(catmapdata)
catmapobject <- catmap(catmapdata, 0.95, TRUE)