--- a
+++ b/man/modtest_ic.Rd
@@ -0,0 +1,56 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/eif_moderated.R
+\name{modtest_ic}
+\alias{modtest_ic}
+\title{Moderated Statistical Tests for Influence Functions}
+\usage{
+modtest_ic(biotmle, adjust = "BH", pval_type = c("normal", "logistic"), ...)
+}
+\arguments{
+\item{biotmle}{\code{biotmle} object as generated by \code{biomarkertmle}}
+
+\item{adjust}{the multiple testing correction to be applied to p-values that
+are generated from the moderated tests. The recommended (default) method
+is that of Benjamini and Hochberg. See \link[limma]{topTable} for a list of
+appropriate methods.}
+
+\item{pval_type}{The reference distribution to be used for computing the
+p-value. Those based on the normal approximation tend to provide misleading
+inference when working with moderately sized (finite) samples. Use of the
+logistic distribution has been found to empirically improve performance in
+settings where multiple hypothesis testing is a concern.}
+
+\item{...}{Other arguments passed to \code{\link[limma]{topTable}}.}
+}
+\value{
+\code{biotmle} object containing the results of applying both
+ \code{\link[limma]{lmFit}} and \code{\link[limma]{topTable}}.
+}
+\description{
+Performs variance shrinkage via application of an empirical Bayes procedure
+(of LIMMA) on the observed data after a transformation moving the data to
+influence function space, based on the average treatment effect parameter.
+}
+\examples{
+library(dplyr)
+library(biotmleData)
+library(SuperLearner)
+library(SummarizedExperiment)
+data(illuminaData)
+
+colData(illuminaData) <- colData(illuminaData) \%>\%
+  data.frame() \%>\%
+  dplyr::mutate(age = as.numeric(age > median(age))) \%>\%
+  DataFrame()
+benz_idx <- which(names(colData(illuminaData)) \%in\% "benzene")
+
+biomarkerTMLEout <- biomarkertmle(
+  se = illuminaData[1:2, ],
+  varInt = benz_idx,
+  bppar_type = BiocParallel::SerialParam(),
+  g_lib = c("SL.mean", "SL.glm"),
+  Q_lib = c("SL.mean", "SL.glm")
+)
+
+limmaTMLEout <- modtest_ic(biotmle = biomarkerTMLEout)
+}