R/report.b.R

In sbalci/histopathology-template: Template of R Codes Used in Histopathology Research.

#' @importFrom R6 R6Class
#' @import jmvcore
#'
# This file is a generated template, your changes will not be overwritten

reportClass <- if (requireNamespace('jmvcore')) R6::R6Class(
    "reportClass",
    inherit = reportBase,
    private = list(
        .run = function() {


            if (length(self$options$vars) == 0) {
                todo <- "
                <br>Welcome to ClinicoPath
                          <br><br>
                          This tool will help you to write a general summary of variables
                              in your data.
                          <br><br>
                          Select the 'Variables' you want to include in the summary. Numeric, Ordinal, and Categorical variables are allowed.
                          <br><br>
                          Use checkboxes to change the output of summary.
                          <br><br>
                          This tool uses report package. Please cite the packages and jamovi using references below.
                          "

                html <- self$results$todo
                html$setContent(todo)
                return()
            } else {

                todo <- "Summary of the data: "
                html <- self$results$todo
                html$setContent(todo)


            mydata <- self$data

            med <- self$options$med

            cent <- self$options$cent

            disp <- self$options$disp

            ran <- self$options$ran

            distr <- self$options$distr

            lev <- self$options$lev

            n_ch <- self$options$n_ch

            mis <- self$options$mis

            formula <- jmvcore::constructFormula(terms = self$options$vars)

            myvars <- jmvcore::decomposeFormula(formula = formula)

            myvars <- unlist(myvars)

            myreport <- mydata %>%
                select(myvars) %>%
                report::report(.
            ,
                               median = med,
                               centrality = cent,
                               dispersion = disp,
                               range = ran,
                               distribution = distr,
                               levels_percentage = lev,
                               n_characters = n_ch,
                               missing_percentage = mis
                               )

            results1 <- myreport



            # results1 <- mydata %>%
            #     explore::describe(.) %>%
            #     dplyr::filter(na > 0)



            self$results$text$setContent(results1)

            }






        })
)