getNormCurve {cNORM} | R Documentation

## Computes the curve for a specific T value

### Description

As with this continuous norming regression approach, raw scores are modeled as a function of age and norm score (location), getNormCurve is a straightforward approach to show the raw score development over age, while keeping the norm value constant. This way, e. g. academic performance or intelligence development of a specific ability is shown.

### Usage

    getNormCurve(
      norm,
      model,
      minAge = NULL,
      maxAge = NULL,
      step = 0.1,
      minRaw = NULL,
      maxRaw = NULL,
      covariate = NULL
    )

### Arguments

`norm` | The specific norm score, e. g. T value
`model` | The model from the regression modeling or a cnorm object
`minAge` | Age to start from
`maxAge` | Age to stop at
`step` | Stepping parameter for the precision when retrieving of the values, lower values indicate higher precision (default 0.1).
`minRaw` | lower bound of the range of raw scores (default = 0)
`maxRaw` | upper bound of raw scores
`covariate` | In case, a covariate has been used, please specify the degree of the covariate or the specific value here.

### Value

data.frame of the variables raw, age and norm

### See Also

Other predict: `derivationTable()`, `normTable()`, `predictNorm()`, `predictRaw()`, `rawTable()`

### Examples

    # Generate cnorm object from example data
    cnorm.elfe <- cnorm(raw = elfe$raw, group = elfe$group)
    getNormCurve(35, cnorm.elfe)

[Package cNORM version 2.0.3 Index]