False discovery rate estimation for massively parallel restricted likelihood ratio tests

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Description

Given a set of RLRT results and a threshold, this function outputs an estimate of the FDR (in the empirical Bayes sense of Efron, 2010) when the given threshold is used to determine which null hypotheses to reject.

Usage

1
Fdr.rlrt(rlrt.obj, threshold)

Arguments

rlrt.obj

an RLRT object obtained from rlrt.mp or rlrt4d.

threshold

threshold at which the null hypothesis is rejected.

Value

A list with elements

MoM

FDR based on method of moments estimator of RLRT parameters (Greven et al., 2008).

ML

FDR based on maximum likelihood estimation of RLRT parameters, as described in Greven et al. (2008).

Author(s)

Philip Reiss phil.reiss@nyumc.org

References

Efron, B. (2010). Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction. New York: Cambridge University Press.

Greven, S., Crainiceanu, C. M., Kuechenhoff, H., and Peters, A. (2008). Restricted likelihood ratio testing for zero variance components in linear mixed models. Journal of Computational and Graphical Statistics, 17(4), 870–891.

See Also

rlrt.mp, rlrt4d

Examples

1
# See example for rlrt.mp

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