R/anovarmnp.h.R

In jamovi/Rjamovi: The 'jamovi' Analyses

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

anovaRMNPOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
    "anovaRMNPOptions",
    inherit = jmvcore::Options,
    public = list(
        initialize = function(
            measures = NULL,
            pairs = FALSE,
            desc = FALSE,
            plots = FALSE,
            plotType = "means", ...) {

            super$initialize(
                package="jmv",
                name="anovaRMNP",
                requiresData=TRUE,
                ...)

            private$..measures <- jmvcore::OptionVariables$new(
                "measures",
                measures,
                suggested=list(
                    "continuous"),
                permitted=list(
                    "numeric"))
            private$..pairs <- jmvcore::OptionBool$new(
                "pairs",
                pairs,
                default=FALSE)
            private$..desc <- jmvcore::OptionBool$new(
                "desc",
                desc,
                default=FALSE)
            private$..plots <- jmvcore::OptionBool$new(
                "plots",
                plots,
                default=FALSE)
            private$..plotType <- jmvcore::OptionList$new(
                "plotType",
                plotType,
                options=list(
                    "means",
                    "medians"),
                default="means")

            self$.addOption(private$..measures)
            self$.addOption(private$..pairs)
            self$.addOption(private$..desc)
            self$.addOption(private$..plots)
            self$.addOption(private$..plotType)
        }),
    active = list(
        measures = function() private$..measures$value,
        pairs = function() private$..pairs$value,
        desc = function() private$..desc$value,
        plots = function() private$..plots$value,
        plotType = function() private$..plotType$value),
    private = list(
        ..measures = NA,
        ..pairs = NA,
        ..desc = NA,
        ..plots = NA,
        ..plotType = NA)
)

anovaRMNPResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
    "anovaRMNPResults",
    inherit = jmvcore::Group,
    active = list(
        table = function() private$.items[["table"]],
        comp = function() private$.items[["comp"]],
        desc = function() private$.items[["desc"]],
        plot = function() private$.items[["plot"]]),
    private = list(),
    public=list(
        initialize=function(options) {
            super$initialize(
                options=options,
                name="",
                title="Repeated Measures ANOVA (Non-parametric)")
            self$add(jmvcore::Table$new(
                options=options,
                name="table",
                title="Friedman",
                rows=1,
                clearWith=list(
                    "measures"),
                columns=list(
                    list(
                        `name`="stat", 
                        `title`="\u03C7\u00B2", 
                        `type`="number"),
                    list(
                        `name`="df", 
                        `title`="df", 
                        `type`="integer"),
                    list(
                        `name`="p", 
                        `title`="p", 
                        `type`="number", 
                        `format`="zto,pvalue"))))
            self$add(jmvcore::Table$new(
                options=options,
                name="comp",
                title="Pairwise Comparisons (Durbin-Conover)",
                refs="PMCMR",
                visible="(pairs)",
                clearWith=list(
                    "measures"),
                columns=list(
                    list(
                        `name`="i1", 
                        `title`="", 
                        `type`="text"),
                    list(
                        `name`="sep", 
                        `title`="", 
                        `content`="-", 
                        `type`="text", 
                        `format`="narrow"),
                    list(
                        `name`="i2", 
                        `title`="", 
                        `type`="text"),
                    list(
                        `name`="stat", 
                        `title`="Statistic", 
                        `type`="number"),
                    list(
                        `name`="p", 
                        `title`="p", 
                        `type`="number", 
                        `format`="zto,pvalue"))))
            self$add(jmvcore::Table$new(
                options=options,
                name="desc",
                title="Descriptives",
                visible="(desc)",
                clearWith=list(
                    "measures"),
                columns=list(
                    list(
                        `name`="level", 
                        `title`="", 
                        `type`="text"),
                    list(
                        `name`="mean", 
                        `title`="Mean", 
                        `type`="number"),
                    list(
                        `name`="median", 
                        `title`="Median", 
                        `type`="number"))))
            self$add(jmvcore::Image$new(
                options=options,
                name="plot",
                title="Descriptive Plot",
                visible="(plots)",
                renderFun=".plot",
                clearWith=list(
                    "plotType",
                    "measures")))}))

anovaRMNPBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
    "anovaRMNPBase",
    inherit = jmvcore::Analysis,
    public = list(
        initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
            super$initialize(
                package = "jmv",
                name = "anovaRMNP",
                version = c(1,0,0),
                options = options,
                results = anovaRMNPResults$new(options=options),
                data = data,
                datasetId = datasetId,
                analysisId = analysisId,
                revision = revision,
                pause = NULL,
                completeWhenFilled = TRUE,
                requiresMissings = FALSE,
                weightsSupport = 'auto')
        }))

#' Repeated Measures ANOVA (Non-parametric)
#'
#' The Friedman test is used to explore the relationship between a continuous 
#' dependent variable and a categorical explanatory variable, where the 
#' explanatory variable is 'within subjects' (where multiple measurements are 
#' from the same subject). It is analagous to Repeated Measures ANOVA, but 
#' with the advantage of being non-parametric, and not requiring the 
#' assumptions of normality or homogeneity of variances. However, it has the 
#' limitation that it can only test a single explanatory variable at a time.
#' 
#'
#' @examples
#' data('bugs', package = 'jmv')
#'
#' anovaRMNP(bugs, measures = vars(LDLF, LDHF, HDLF, HDHF))
#'
#' #
#' #  REPEATED MEASURES ANOVA (NON-PARAMETRIC)
#' #
#' #  Friedman
#' #  ------------------------
#' #    X²      df    p
#' #  ------------------------
#' #    55.8     3    < .001
#' #  ------------------------
#' #
#'
#' @param data the data as a data frame
#' @param measures a vector of strings naming the repeated measures variables
#' @param pairs \code{TRUE} or \code{FALSE} (default), perform pairwise
#'   comparisons
#' @param desc \code{TRUE} or \code{FALSE} (default), provide descriptive
#'   statistics
#' @param plots \code{TRUE} or \code{FALSE} (default), provide a descriptive
#'   plot
#' @param plotType \code{'means'} (default) or \code{'medians'}, the error
#'   bars to use in the plot
#' @return A results object containing:
#' \tabular{llllll}{
#'   \code{results$table} \tab \tab \tab \tab \tab a table of the Friedman test results \cr
#'   \code{results$comp} \tab \tab \tab \tab \tab a table of the pairwise comparisons \cr
#'   \code{results$desc} \tab \tab \tab \tab \tab a table containing the descriptives \cr
#'   \code{results$plot} \tab \tab \tab \tab \tab a descriptives plot \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$table$asDF}
#'
#' \code{as.data.frame(results$table)}
#'
#' @export
anovaRMNP <- function(
    data,
    measures,
    pairs = FALSE,
    desc = FALSE,
    plots = FALSE,
    plotType = "means") {

    if ( ! requireNamespace("jmvcore", quietly=TRUE))
        stop("anovaRMNP requires jmvcore to be installed (restart may be required)")

    if ( ! missing(measures)) measures <- jmvcore::resolveQuo(jmvcore::enquo(measures))
    if (missing(data))
        data <- jmvcore::marshalData(
            parent.frame(),
            `if`( ! missing(measures), measures, NULL))


    options <- anovaRMNPOptions$new(
        measures = measures,
        pairs = pairs,
        desc = desc,
        plots = plots,
        plotType = plotType)

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

    analysis$run()

    analysis$results
}