R/coef.glca.R

In glca: An R Package for Multiple-Group Latent Class Analysis

#' Extracts \code{glca} Model Coefficients
#'
#' Extracts regression coefficients of \code{glca} model if the model includes covariates.
#'
#' @param object an object of "\code{glca}".
#' @param intercept a logical value for whether to print intercept".
#' @param digits number of significant digits to use when printing.
#' @param show.signif.stars logical. If TRUE, ‘significance stars’ are printed for each coefficient.
#' @param ... further arguments passed to or from other methods.
#'
#' @return Coefficient matrix from the \code{glca} model
#'
#' If the model has calculated standard errors, coefficient matrix contains standard errors, t-statistic, and its p-value.
#'
#' @seealso \code{\link{glca}}
#'
#' @examples
#' ## For examples see example(glca)
#'
#' @method coef glca
#' @export

coef.glca = function(
   object, intercept = FALSE, digits = max(3, getOption("digits") - 3),
   show.signif.stars = getOption("show.signif.stars"), ...
)
{
   if (is.null(object$param$beta))
      return(NULL)
   else {
      if (object$model$coeff.inv) {
         coef = object$coefficient
         if (object$model$W > 1) {
            if (intercept) {
               cat("Intercept :\n\n")
               intmat = lapply(1:object$model$W, function(w) {
                  mat = t(sapply(1:(object$model$C - 1), function(c) coef[[1]][[w]][[c]][1,]))
                  rownames(mat) = paste("Class", 1:(object$model$C - 1), "/", object$model$C)
                  as.data.frame(mat)
               })

               for (w in 1:object$model$W) {
                  cat("Cluster", w, ":\n")
                  stats::printCoefmat(intmat[[w]],
                                      digits = digits,
                                      signif.stars = getOption("show.signif.stars"),
                                      P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            }

            if (object$model$P > 1) {
               cat("\nLevel 1 Coefficients :\n\n")
               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  coefmat = coef[[1]][[1]][[c]][2:object$model$P,]
                  stats::printCoefmat(coefmat,
                                      digits = digits,
                                      signif.stars = getOption("show.signif.stars"),
                                      P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            }

            if (object$model$Q > 0) {
               cat("\nLevel 2 Coefficients :\n\n")
               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  if (is.null(object$convergence$score))
                     print(coef[[2]][[c]])
                  else
                     stats::printCoefmat(coef[[2]][[c]],
                                         digits = digits,
                                         signif.stars = getOption("show.signif.stars"),
                                         P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            }
         } else {
            if (object$model$G == 1) {
               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  if (is.null(object$convergence$score))
                     print(coef[[1]][[c]])
                  else
                     stats::printCoefmat(coef[[1]][[c]],
                                         digits = digits,
                                         signif.stars = getOption("show.signif.stars"),
                                         P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            } else {
               if (intercept) {
                  cat("Intercept :\n\n")
                  intmat = lapply(1:object$model$G, function(g) {
                     mat = t(sapply(1:(object$model$C - 1), function(c) coef[[g]][[c]][1,]))
                     rownames(mat) = paste("Class", 1:(object$model$C - 1), "/", object$model$C)
                     as.data.frame(mat)
                  })
                  for (g in 1:object$model$G) {
                     cat("Group ", object$var.names$g.names[g], ":\n", sep = "")
                     stats::printCoefmat(intmat[[g]],
                                         digits = digits,
                                         signif.stars = getOption("show.signif.stars"),
                                         P.values = TRUE, has.Pvalue = TRUE)
                     cat("\n")
                  }
               }

               cat("Coefficients :\n\n")
               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  coefmat = coef[[1]][[c]][2:object$model$P,]
                  stats::printCoefmat(coefmat,
                                      digits = digits,
                                      signif.stars = getOption("show.signif.stars"),
                                      P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            }
         }
      } else {
         coef = object$coefficient
         if (object$model$W > 1) {
            cat("Level 1 Coefficients :\n\n")
            for (w in 1:object$model$W) {
               cat("Cluster", w, ":\n")

               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  if (is.null(object$convergence$score))
                     print(coef[[1]][[w]][[c]])
                  else
                     stats::printCoefmat(coef[[1]][[w]][[c]],
                                         digits = digits,
                                         signif.stars = getOption("show.signif.stars"),
                                         P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
               cat("\n")
            }
            if (object$model$Q > 0) {
               cat("\nLevel 2 Coefficients :\n\n")
               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  if (is.null(object$convergence$score))
                     print(coef[[2]][[c]])
                  else
                     stats::printCoefmat(coef[[2]][[c]],
                                         digits = digits,
                                         signif.stars = getOption("show.signif.stars"),
                                         P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            }
         } else {
            if (object$model$G == 1) {
               for (c in 1:(object$model$C - 1)) {
                  cat("Class", c, "/", object$model$C, ":\n")
                  if (is.null(object$convergence$score))
                     print(coef[[1]][[c]])
                  else
                     stats::printCoefmat(coef[[1]][[c]],
                                         digits = digits,
                                         signif.stars = getOption("show.signif.stars"),
                                         P.values = TRUE, has.Pvalue = TRUE)
                  cat("\n")
               }
            } else {
               for (g in 1:object$model$G) {
                  cat("Group ", object$var.names$g.names[g], ":\n", sep = "")

                  for (c in 1:(object$model$C - 1)) {
                     cat("Class", c, "/", object$model$C, ":\n")
                     if (is.null(object$convergence$score))
                        print(coef[[g]][[c]])
                     else
                        stats::printCoefmat(coef[[g]][[c]],
                                            digits = digits,
                                            signif.stars = getOption("show.signif.stars"),
                                            P.values = TRUE, has.Pvalue = TRUE)
                     cat("\n")
                  }
                  cat("\n")
               }
            }
         }
      }

      invisible(coef)
   }
}