This function generates cross tables comparing a dependent variable (rows) with a grouping variable (columns) and automatically selects hypothesis tests appropriate for clinical research. The output tables are rendered in various styles (e.g., arsenal, finalfit, gtsummary, NEJM, Lancet, hmisc) and are intended for pathologists and oncologists. In addition to visualizing associations, this function now optionally provides an exportable CSV version of the cross table.
Value
The function produces an HTML table output, and if requested, an additional downloadable CSV export.
Details
The function cleans variable names and applies original labels. It then builds a formula based on the cleaned data and performs the appropriate statistical test (e.g. chi-square or Fisher’s exact test). Detailed user guidance is provided via HTML to-do messages.
Super classes
jmvcore::Analysis -> ClinicoPath::crosstableBase -> crosstableClass
Methods
Inherited methods
jmvcore::Analysis$.createImage()jmvcore::Analysis$.createImages()jmvcore::Analysis$.createPlotObject()jmvcore::Analysis$.load()jmvcore::Analysis$.render()jmvcore::Analysis$.save()jmvcore::Analysis$.savePart()jmvcore::Analysis$.setCheckpoint()jmvcore::Analysis$.setParent()jmvcore::Analysis$.setReadDatasetHeaderSource()jmvcore::Analysis$.setReadDatasetSource()jmvcore::Analysis$.setResourcesPathSource()jmvcore::Analysis$.setStatePathSource()jmvcore::Analysis$addAddon()jmvcore::Analysis$asProtoBuf()jmvcore::Analysis$asSource()jmvcore::Analysis$check()jmvcore::Analysis$init()jmvcore::Analysis$optionsChangedHandler()jmvcore::Analysis$postInit()jmvcore::Analysis$print()jmvcore::Analysis$readDataset()jmvcore::Analysis$run()jmvcore::Analysis$serialize()jmvcore::Analysis$setError()jmvcore::Analysis$setStatus()jmvcore::Analysis$translate()ClinicoPath::crosstableBase$initialize()