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NRejections (version 1.2.0)

Metrics for Multiple Testing with Correlated Outcomes

Description

Implements methods in Mathur and VanderWeele (in preparation) to characterize global evidence strength across W correlated ordinary least squares (OLS) hypothesis tests. Specifically, uses resampling to estimate a null interval for the total number of rejections in, for example, 95% of samples generated with no associations (the global null), the excess hits (the difference between the observed number of rejections and the upper limit of the null interval), and a test of the global null based on the number of rejections.

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Version

Install

install.packages('NRejections')

Monthly Downloads

185

Version

1.2.0

License

GPL-2

Maintainer

Maya Mathur

Last Published

July 9th, 2020

Functions in NRejections (1.2.0)

get_crit

Return ordered critical values for Wstep
resample_resid

Resample residuals for OLS
fit_model

Fit OLS model for a single outcome
fix_input

Fix bad user input
adj_Wstep

Return Wstep-adjusted p-values
cell_corr

Cell correlation for simulating data
sim_data

Simulate MVN data
adj_minP

Adjust p-values using minP
corr_tests

Global evidence strength across correlated tests
dataset_result

Fit all models for a single dataset
make_corr_mat

Makes correlation matrix to simulate data