tidy_results.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/waldtest.R
\name{tidy_results}
\alias{tidy_results}
\title{Perform statistical tests and return tidy results}
\usage{
tidy_results(
  list_tmb,
  coeff_threshold = 0,
  alternative_hypothesis = "greaterAbs",
  correction_method = "BH"
)
}
\arguments{
\item{list_tmb}{A list of glmmTMB objects representing the fitted models.}

\item{coeff_threshold}{A non-negative value which specifies a ln(fold change) threshold. The Threshold  is used for the Wald test to determine whether the  coefficient (β) is significant or not, depending on \code{alt_hypothesis} parameter. Default is 0, ln(FC = 1).}

\item{alternative_hypothesis}{Alternative hypothesis for the Wald test (default is "greaterAbs").
Possible choice:
"greater"
\itemize{
\item β > coeff_threshold,
"less"
\item β < −coeff_threshold,
or two-tailed alternative:
"greaterAbs"
\item |β| > coeff_threshold
}}

\item{correction_method}{a character string indicating the correction method to apply to p-values. Possible values are:
"holm", "hochberg", "hommel", #' "bonferroni", "BH", "BY", "fdr", and "none".}
}
\value{
A tidy data frame containing the results of statistical tests for the estimated coefficients.
}
\description{
This function takes a list of glmmTMB objects and performs statistical tests based on the estimated coefficients and their standard errors. The results are returned in a tidy data frame format.
}
\examples{
data(iris)
model_list <- fitModelParallel(formula = Sepal.Length ~ Sepal.Width + Petal.Length, 
                 data = iris, group_by = "Species", n.cores = 1) 
results_df <- tidy_results(model_list, coeff_threshold = 0.1, alternative_hypothesis = "greater")
}