plotNorm {cNORM} | R Documentation

## Plot manifest and fitted norm scores

### Description

The function plots the manifest norm score against the fitted norm score from the inverse regression model per group. This helps to inspect the precision of the modeling process. The scores should not deviate too far from regression line. The computation of the standard error is based on Oosterhuis, van der Ark and Sijtsma (2016).

### Usage

    plotNorm(data, model, group = "", minNorm = NULL, maxNorm = NULL, type = 0)

### Arguments

`data` | The raw data within a data.frame or a cnorm object
`model` | The regression model (optional)
`group` | The grouping variable, use empty string for no group
`minNorm` | lower bound of fitted norm scores
`maxNorm` | upper bound of fitted norm scores
`type` | Type of display: 0 = plot manifest against fitted values, 1 = plot manifest against difference values

### References

Oosterhuis, H. E. M., van der Ark, L. A., & Sijtsma, K. (2016). Sample Size Requirements for Traditional and Regression-Based Norms. Assessment, 23(2), 191–202. https://doi.org/10.1177/1073191115580638

### See Also

Other plot: `plot.cnorm()`, `plotDensity()`, `plotDerivative()`, `plotNormCurves()`, `plotPercentileSeries()`, `plotPercentiles()`, `plotRaw()`, `plotSubset()`

### Examples

    # Load example data set, compute model and plot results
    ## Not run:
    result <- cnorm(raw = elfe$raw, group = elfe$group)
    plotNorm(result, group="group", minNorm=25, maxNorm=75)

    ## End(Not run)

[Package cNORM version 2.0.3 Index]