cNORM (version 2.0.1)

plotNorm: 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<U+2013>202. https://doi.org/10.1177/1073191115580638

See Also

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

Examples

# NOT RUN {
# 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)
# }