Description Usage Arguments Details Value Author(s) References Examples
An implementaiton of the conditional local false discovery rate procedure of
Cai and Sun (2009). This is a near copy of the implementation provided in the
IHWpaper package, clfdr
at
the corresponding GitHub repo,
written by Nikos Ignatiadis and made available under the GPL-3 license.
The original code has been modified to only return a vector of adjusted
p-values and check the input of the lfdr_estimation=
parameter.
1 |
p |
numeric vector of unadjusted p-values. |
groups |
factor to which different hypotheses belong. |
lfdr_estimation |
method used to estimate the local fdr; must be one of "fdrtool" or "locfdr". (default = "fdrtool") |
If the covariate or variable for stratifying p-values is continuous, it should
be converted into a discrete set of "groups" before applying this function.
This can be accomplished by passing the continuous variable to IHW::groups_by_filter
,
ggplot2::cut_number
, or any similar function. See examples for
uses of these functions.
Numeric vector of adjusted p-values of equal length and order as the to input vector of p-values.
Patrick Kimes
Reference for the conditional local false discovery rate (underlying theory):
Cai, T.T., Sun, W. (2009) Simultaneous testing of grouped hypotheses: Finding needles in multiple haystacks. Journal of the American Statistical Association, 104(488):1467-1481. https://doi.org/10.1198/jasa.2009.tm08415
Reference for the original implementation (underlying code):
Ignatiadis, N. (2017) IHWpaper: Reproduce figures in IHW paper. R package version 1.7.0. https://doi.org/doi:10.18129/B9.bioc.IHWpaper
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