R/repeated.h.R

In rivkamdevries/Statkat: Statkat - Method Selection Tool

# This file is automatically generated, you probably don't want to edit this

repeatedOptions <- if (requireNamespace('jmvcore')) R6::R6Class(
    "repeatedOptions",
    inherit = jmvcore::Options,
    public = list(
        initialize = function(
            variables = NULL, ...) {

            super$initialize(
                package='Statkat',
                name='repeated',
                requiresData=TRUE,
                ...)

            private$..variables <- jmvcore::OptionVariables$new(
                "variables",
                variables)

            self$.addOption(private$..variables)
        }),
    active = list(
        variables = function() private$..variables$value),
    private = list(
        ..variables = NA)
)

repeatedResults <- if (requireNamespace('jmvcore')) R6::R6Class(
    inherit = jmvcore::Group,
    active = list(
        advice = function() private$.items[["advice"]],
        plot = function() private$.items[["plot"]]),
    private = list(),
    public=list(
        initialize=function(options) {
            super$initialize(
                options=options,
                name="",
                title="Repeated Measurements")
            self$add(jmvcore::Html$new(
                options=options,
                name="advice",
                title="Advice",
                visible="(text)"))
            self$add(jmvcore::Image$new(
                options=options,
                name="plot",
                title="Scatter Plot",
                width=400,
                height=300,
                requiresData=TRUE,
                renderFun=".plot"))}))

repeatedBase <- if (requireNamespace('jmvcore')) R6::R6Class(
    "repeatedBase",
    inherit = jmvcore::Analysis,
    public = list(
        initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
            super$initialize(
                package = 'Statkat',
                name = 'repeated',
                version = c(1,0,0),
                options = options,
                results = repeatedResults$new(options=options),
                data = data,
                datasetId = datasetId,
                analysisId = analysisId,
                revision = revision,
                pause = NULL,
                completeWhenFilled = TRUE)
        }))

#' Repeated Measurements
#'
#' Provides a recommended statistical method given the measurement level of 
#' your data. Appropriate for repeated measurements.
#'
#' @examples
#' exampleData <- data.frame(x1 = rnorm(20),
#'                           x2 = rnorm(20),
#'                           x3 = rnorm(20),
#'                           x4 = as.factor(c(rep(1, 10), rep(2, 10))),
#'                           x5 = as.factor(c(rep(1, 5), rep(2, 5), rep(3, 10))),
#'                           x6 = as.ordered(c(rep(1, 5), rep(2, 5), rep(3, 10))),
#'                           x7 = as.ordered(c(rep(1, 10), rep(2, 5), rep(3, 5))))
#'
#' repeated(exampleData, variables = c('x1', 'x2', 'x3'))
#' repeated(exampleData, variables = c('x4', 'x5'))
#' repeated(exampleData, variables = c('x6', 'x7'))
#'
#' @param data the data as a data frame, with variables encoded as numeric
#'   (for interval/ratio variables), ordered (for ordinal variables), or factor
#'   (for nominal variables)
#' @param variables a vector of strings naming the related variables from
#'   \code{data}
#' @return A results object containing:
#' \tabular{llllll}{
#'   \code{results$advice} \tab \tab \tab \tab \tab the method recommendation \cr
#'   \code{results$plot} \tab \tab \tab \tab \tab a scatter plot of the data \cr
#' }
#'
#' @export
repeated <- function(
    data,
    variables) {

    if ( ! requireNamespace('jmvcore'))
        stop('repeated requires jmvcore to be installed (restart may be required)')

    options <- repeatedOptions$new(
        variables = variables)

    results <- repeatedResults$new(
        options = options)

    analysis <- repeatedClass$new(
        options = options,
        data = data)

    analysis$run()

    analysis$results
}