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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