f.Q: Compute Cochran's Q statistic

In Bioconductor/GeneMeta: MetaAnalysis for High Throughput Experiments

Compute Cochran's Q statistic

Description

Compute Cochran's Q statistic for testing whether the a fixed effects or a random effects model will be appropriate.

Usage

f.Q(dadj, varadj)

Arguments

dadj	A matrix, each row is a gene, each column a study, of the estimated t-statistics.
varadj	A matrix, each row is a gene, each column a study, of the estimated, adjusted variances of the t-statistics.

Details

A straightforward computation of Cochran's Q statistic. If the null hypothesis that the data are well modeled by a fixed effects design is true then the estimate Q values will have approximately a chi-squared distribution with degrees of freedom equal to the number of studies minus one.

Value

A vector of length equal to the number of rows of dadj with the Q statistics.

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

##none now, this requires a pretty elaborate example

Bioconductor/GeneMeta documentation built on Nov. 2, 2024, 6:35 a.m.