R/coefa_gcm.R

In coefa: Meta Analysis of Factor Analysis Based on CO-Occurrence Matrices

#' Generate co-occurrence matrices
#'
#'The co-occurrence matrices are generated by this function. This function can
#' be used obtain the co-occurrence matrix for each primary study.
#' @param x A list containing multiple trimmed factor loading matrices
#' @param ... Additional parameters which generate the co-occurrence matrices.
#' @details The meta-analysts can use this function to obtain the co-occurrence
#' matrix for each primary study. And the algorithm is that a trimmed factor
#' loading matrix multiplies its transpose in the list. As a result, the number
#' of the dimension of the matrix obtained in this step equates with that of
#' the items included in a scale. In this new matrix, the values on the
#' cross-cells indicate the clusters of the items. The greater the value in
#' the cross-cells of a co-occurrence matrix, the bigger the degree of similarity
#' between paired items.
#'
#' @return A list containing multiple co-occurrence matrices.
#' @export
#'
#' @references
#' Shafer,A. B.(2005). Meta-analysis of the Brief Psychiatric Rating Scale
#' factor structure. Psychological Assessment, 17(3),324--335.
#'
#' Shafer,A. B. (2006). Meta-analysis of the factor structures of four depression
#'  questionnaires: Beck, CES-D, Hamilton, and Zung. Journal of clinical
#'  psychology, 62(1), 123--146.
#'
#' @examples
#' \donttest{#Suppose that the matrices.tflm is the factor loading matrices trimmed.
#' #Note:This is just an example.
#' #The real co-occurrence matrix should be generated from actual studies.
#' mx1.tflm<-matrix(c(1,0,0,1,1,0),nrow=2,byrow=2)
#' mx2.tflm<-matrix(c(1,0,0,1),nrow=2,byrow=2)
#' matrices.tflm<-list(mx1.tflm,mx2.tflm)
#' #Generate co-occurrence matrices.
#' matrices.gcm<-coefa_gcm(matrices.tflm)}
coefa_gcm<-function(x,...){
  #generate co-occurrence matrices
  xz<-function(x){
    xlq<-x%*%t(x)
    return(xlq)
  }
  for(i in 1:length(x)){
    x[[i]]<-as.matrix(x[[i]])
    x[[i]]<-xz(x[[i]])
  }
  re3<-x
  return(re3)
}