Package: pwrFDR
Version: 3.2.4
Title: FDR Power
Authors@R: person("Grant", "Izmirlian", role=c("aut", "cre"),
                  email="izmirlig@mail.nih.gov")
Imports: flextable, ggplot2, methods, mvtnorm, stats, stringr,
        TableMonster
Description: Computing Average and TPX Power under various BHFDR type
        sequential procedures. All of these procedures involve control
        of some summary of the distribution of the FDP, e.g. the
        proportion of discoveries which are false in a given
        experiment. The most widely known of these, the BH-FDR
        procedure, controls the FDR which is the mean of the FDP. A
        lesser known procedure, due to Lehmann and Romano, controls the
        FDX, or probability that the FDP exceeds a user provided
        threshold. This is less conservative than FWE control
        procedures but much more conservative than the BH-FDR
        proceudre. This package and the references supporting it
        introduce a new procedure for controlling the FDX which we call
        the BH-FDX procedure. This procedure iteratively identifies,
        given alpha and lower threshold delta, an alpha* less than
        alpha at which BH-FDR guarantees FDX control.  This uses
        asymptotic approximation and is only slightly more conservative
        than the BH-FDR procedure. Likewise, we can think of the power
        in multiple testing experiments in terms of a summary of the
        distribution of the True Positive Proportion (TPP), the portion
        of tests truly non-null distributed that are called
        significant. The package will compute power, sample size or any
        other missing parameter required for power defined as (i) the
        mean of the TPP (average power) or (ii) the probability that
        the TPP exceeds a given value, lambda, (TPX power) via
        asymptotic approximation. All supplied theoretical results are
        also obtainable via simulation. The suggested approach is to
        narrow in on a design via the theoretical approaches and then
        make final adjustments/verify the results by simulation. The
        theoretical results are described in Izmirlian, G (2020)
        Statistics and Probability letters,
        "<doi:10.1016/j.spl.2020.108713>", and an applied paper
        describing the methodology with a simulation study is in
        preparation. See citation("pwrFDR").
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2026-10-11 09:54:04 UTC; root
Author: Grant Izmirlian [aut, cre]
Maintainer: Grant Izmirlian <izmirlig@mail.nih.gov>
Config/pak/sysreqs: libcairo2-dev cmake libfontconfig1-dev
        libfreetype6-dev libfribidi-dev make libharfbuzz-dev libicu-dev
        libjpeg-dev libpng-dev libtiff-dev libuv1-dev libwebp-dev
        libxml2-dev libssl-dev
Repository: https://izmirlig.r-universe.dev
Date/Publication: 2025-01-14 17:10:02 UTC
RemoteUrl: https://github.com/cran/pwrFDR
RemoteRef: HEAD
RemoteSha: 292071f22f1f235794944b0d9cc69aa3fa49450d
Depends: R (>= 4.1.0)