R/within_variance_comp_emmeans.R

In mariechion/mi4p: Multiple Imputation for Proteomics

#' @title Multiple Imputation Within Variance Component
#' 
#' @description Computes the multiple imputation within variance component using the emmeans package.
#'
#' @param ind index 
#' @param peptide name of the peptide
#' @param data dataset
#' @param metacond a factor to specify the groups
#'
#' @return A variance-covariance matrix.
#' 
#' @author Frédéric Bertrand
#' 
#' @references M. Chion, Ch. Carapito and F. Bertrand (2021). \emph{Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics}.  \doi{doi:10.1371/journal.pcbi.1010420}.
#' @export
#'
#' @examples
#' library(mi4p)
#' data(datasim)
#' datasim_imp <- multi.impute(data = datasim[,-1], conditions = 
#' attr(datasim,"metadata")$Condition, method = "MLE")
#' within_variance_comp_emmeans(1,1,datasim_imp,
#' attr(datasim,"metadata")$Condition)
within_variance_comp_emmeans = function(ind,peptide,data,metacond){
  tempdata <- cbind(reponse=data[peptide,,ind],data.frame(fact=factor(metacond)))
  templm <- lm(reponse~fact,data=tempdata)
  return(vcov((emmeans::emmeans(templm,specs = "fact"))))
}