forestPlot,ModelComparison-method {PDATK} | R Documentation

## Render a forest plot from the `validationStats` slot of a `PCOSP` model object.

### Description

Render a forest plot from the `validationStats` slot of a `PCOSP` model object.

### Usage

    ## S4 method for signature 'ModelComparison'
    forestPlot(
      object,
      stat,
      groupBy = "cohort",
      colourBy = "model",
      vline,
      ...,
      xlab,
      ylab,
      transform,
      colours,
      title
    )

### Arguments

`object` | A `ModelComparison` object to forest plot.
`stat` | A `character` vector specifying a statistic to plot.
`groupBy` | A `character` vector with one or more columns in `validationStats` to group by. These will be the facets in your forestplot.
`colourBy` | A `character` vector specifying the columns in `validationStats` to colour by.
`vline` | An `integer` value on the x-axis to place a dotted vertical line.
`...` | Force subsequent parameters to be named, not used.
`xlab` | A `character` vector specifying the desired x label. Automatically guesses based on the `stat` argument.
`ylab` | A `character` vector specifying the desired y label. Defaults to 'Cohort (P-value)'.
`transform` | The name of a numeric function to transform the statistic before making the forest plot.
`colours` | A `character` vector of colours to pass into `ggplot2::scale_fill_manual`, which modify the colourBy argument.
`title` | A `character` vector with a title to add to the plot.

### Value

A `ggplot2` object.

### Examples

    data(sampleValPCOSPmodel)
    data(sampleClinicalModel)
    data(sampleCohortList)

    # Set parallelization settings
    BiocParallel::register(BiocParallel::SerialParam())

    # Train the models
    trainedClinicalModel <- trainModel(sampleClinicalModel)

    # Predict risk/risk-class
    ClinicalPredCohortL <- predictClasses(sampleCohortList[c('PCSI', 'TCGA')],
      model=trainedClinicalModel)

    # Validate the models
    validatedClinicalModel <- validateModel(trainedClinicalModel,
      valData=ClinicalPredCohortL)

    # Compare the models
    modelComp <- compareModels(sampleValPCOSPmodel, validatedClinicalModel)

    # Make the forest plot
    modelComp <- modelComp[modelComp$isSummary == TRUE, ]
    modelCindexCompForestPlot <- forestPlot(modelComp, stat='concordance_index')

[Package PDATK version 1.2.0 Index]