tau: estimating my and tau in a REM

In GeneMeta: MetaAnalysis for High Throughput Experiments

Description

tau2.DL is an estimation of tau in a random effects model (REM) using Cochran's Q statistic.

Usage

tau2.DL(Q, num.studies, my.weights)
mu.tau2(my.d, my.vars.new)
var.tau2(my.vars.new)

Arguments

Q	A vector of Cochran's Q statistics.
num.studies	The number of studies used for the meta-analysis.
my.weights	A matrix with one column for each experiment containing the variances of the effects that should be combined.
my.d	A matrix, with one column for each experiment, containing the effects that should be combined.
my.vars.new	A matrix, with one column for each experiment, containing the variances of the effects that should be combined.

Author(s)

L. Lusa and R. Gentleman

References

Choi et al, Combining multiple microarray studies and modeling interstudy variation. Bioinformatics, 2003, i84-i90.

See Also

dstar,sigmad

Examples

# please have a look at the vignette

GeneMeta documentation built on Nov. 8, 2020, 7:58 p.m.