predictClasses,SurvivalExperiment,ClinicalModel-method {PDATK} | R Documentation

## Predict Survival Prognosis Classes and Risk Scores for A `SurvivalModel` Using a `ClinicalModel` Object.

### Description

Predict Survival Prognosis Classes and Risk Scores for A `SurvivalModel` Using a `ClinicalModel` Object.

### Usage

    ## S4 method for signature 'SurvivalExperiment,ClinicalModel'
    predictClasses(object, model, ..., na.action = "na.exclude", type = "response")

### Arguments

`object` | A `SurvivalExperiment` object with the correct columns in `colData` to match the formula for the `ClinicalModel` object.
`model` | A trained `ClinicalModel` object, as return by `trainModel`.
`...` | Fall through parameters to `stats::predict`.
`na.action` | The `na.action` paramter passed to `stats::predict.glm`.
`type` | The `type` parameter passed to `stats::predict.glm`

### Value

A `SurvivalExperiment` with the model predictions in the colData slot as clinical_prob_good.

### Examples

    data(sampleClinicalModel)
    data(samplePCSIsurvExp)

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

    # Train Model
    trainedClinicalModel <- trainModel(sampleClinicalModel)

    # Make predictions
    ClinicalPredSurvExp <- predictClasses(samplePCSIsurvExp,
      model=trainedClinicalModel)
    head(colData(ClinicalPredSurvExp))

[Package PDATK version 1.2.0 Index]