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.
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
See Also
Other plot:
plot.cnorm(),
plotDensity(),
plotDerivative(),
plotNormCurves(),
plotPercentileSeries(),
plotPercentiles(),
plotRaw(),
plotSubset()
# Load example data set, compute model and plot resultsif (FALSE) {
result <- cnorm(raw = elfe$raw, group = elfe$group)
plotNorm(result, group="group", minNorm=25, maxNorm=75)
}