R/mmlcr_to_lctm.R

In hlennon/LCTMtools: Latent Class Trajectory Models: Tools for checking adequacy

#' Converts an R mmclr model output to the format of R's hlme class
#'
#' @param model contains model parameter estimates and maximised likelihood, AIC, BIC values
#' @return  A format to feed into the LCTMtoolkit() R function
#' @examples
#' \dontrun{mmlcr_to_lctm(model)}
#' @export

mmlcr_to_lctm <- function(model) {
    mod <- list(NULL)
    n <- length(unique(model$components[[1]]$data$ident))
    K <- ncol(model$post.prob) - 1
    
    mod$pprob <- as.data.frame(model$post.prob[, c("groupe", paste0("PostProb", 
        1:K, sep = ""))])
    mod$pprob <- data.frame(ID = row.names(model$post.prob), mod$pprob)
    colnames(mod$pprob) <- c("ID", "class", paste0("prob", 1:K, sep = ""))
    
    mod$call <- "Rmmlcr"
    mod$par <- exp(model$gamma.matrix)/(sum(exp(c(model$gamma.matrix))))
    mod$n <- n
    mod$K <- K
    mod$logLik <- model$loglikelihood
    mod$BIC <- model$BIC
    mod$AIC <- model$AIC
    mod$best <- unlist(model$components[[1]]$coef)
    
    return(mod)
}
# os$PI/100 exp(c(M$best[1:4], 0))/(sum(exp(c(M$best[1:4], 0))))