Metrics for Multiple Testing with Correlated Outcomes
Adjust p-values using minP
Return Wstep-adjusted p-values
Cell correlation for simulating data
Global evidence strength across correlated tests
Fit all models for a single dataset
Fit OLS model for a single outcome
Fix bad user input
Return ordered critical values for Wstep
Makes correlation matrix to simulate data
Resample residuals for OLS
Simulate MVN data
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.