### nobs.R ---
##----------------------------------------------------------------------
## Author: Brice Ozenne
## Created: mar 5 2021 (21:41)
## Version:
## Last-Updated: aug 8 2024 (13:32)
## By: Brice Ozenne
## Update #: 32
##----------------------------------------------------------------------
##
### Commentary:
##
### Change Log:
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##
### Code:
## * nobs.lmm
##' @title Number of Observations from a Linear Mixed Model
##' @description Extract the number of observations from a Linear Mixed Model.
##'
##' @param object a \code{lmm} object.
##' @param ... Not used. For compatibility with the generic method.
##'
##' @return A vector with 4 elements: \itemize{
##' \item \code{obs}: the number of repetitions with full data
##' \item \code{cluster}: the number of clusters with a least one repetition with full data
##' \item \code{missing.obs}: the number of repetitions with missing data
##' \item \code{missing.cluster}: the number of cluster with only missing data
##' }
##' @keywords methods
##' @export
nobs.lmm <- function(object, ...){
## ** normalize user imput
dots <- list(...)
if("options" %in% names(dots) && !is.null(dots$options)){
options <- dots$options
}
dots$options <- NULL
if(length(dots)>0){
stop("Unknown argument(s) \'",paste(names(dots),collapse="\' \'"),"\'. \n")
}
## ** extract
return(c(obs = length(object$design$Y), ## number of observations without missing data
cluster = length(object$design$index.cluster), ## number of cluster with a least one observed data
missing.obs = length(object$index.na),
missing.cluster = sum(is.na(object$cluster$index))
)
)
}
## * nobs.mlmm
##' @title Number of Observations from Multiple Linear Mixed Models
##' @description Extract the number of observations from multiple linear mixed models.
##'
##' @param object a \code{mlmm} object.
##' @param ... Not used. For compatibility with the generic method.
##'
##' @return A matrix with as many rows as models and 4 columns: \itemize{
##' \item \code{obs}: the number of repetitions with full data
##' \item \code{cluster}: the number of clusters with a least one repetition with full data
##' \item \code{missing.obs}: the number of repetitions with missing data
##' \item \code{missing.cluster}: the number of cluster with only missing data
##' }
##' @keywords methods
##' @export
nobs.mlmm <- function(object, ...){
## ** normalize user imput
dots <- list(...)
if("options" %in% names(dots) && !is.null(dots$options)){
options <- dots$options
}
dots$options <- NULL
if(length(dots)>0){
stop("Unknown argument(s) \'",paste(names(dots),collapse="\' \'"),"\'. \n")
}
## ** extract
out <- do.call(rbind,lapply(object$model, stats::nobs))
## ** export
return(out)
}
##----------------------------------------------------------------------
### nobs.R ends here
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