plotDerivative: Plot first order derivative of regression model

In cNORM: Continuous Norming

Plot first order derivative of regression model

Description

This function plots the scores obtained via the first order derivative of the regression model in dependence of the norm score.

Usage

plotDerivative(
  model,
  minAge = NULL,
  maxAge = NULL,
  minNorm = NULL,
  maxNorm = NULL,
  stepAge = NULL,
  stepNorm = NULL,
  order = 1
)

Arguments

model	The model from the bestModel function, a cnorm object.
minAge	Minimum age to start checking. If NULL, it's automatically determined from the model.
maxAge	Maximum age for checking. If NULL, it's automatically determined from the model.
minNorm	Lower end of the norm score range. If NULL, it's automatically determined from the model.
maxNorm	Upper end of the norm score range. If NULL, it's automatically determined from the model.
stepAge	Stepping parameter for the age check, usually 1 or 0.1; lower values indicate higher precision.
stepNorm	Stepping parameter for norm scores.
order	Degree of the derivative (default = 1).

Details

The results indicate the progression of the norm scores within each age group. The regression-based modeling approach relies on the assumption of a linear progression of the norm scores. Negative scores in the first order derivative indicate a violation of this assumption. Scores near zero are typical for bottom and ceiling effects in the raw data.

The regression models usually converge within the range of the original values. In case of vertical and horizontal extrapolation, with increasing distance to the original data, the risk of assumption violation increases as well.

Value

A ggplot object representing the derivative of the regression function.

Note

This function is currently incompatible with reversed raw score scales ('descent' option).

See Also

checkConsistency, bestModel, derive

Other plot: compare(), plot.cnorm(), plot.cnormBetaBinomial(), plot.cnormBetaBinomial2(), plotDensity(), plotNorm(), plotNormCurves(), plotPercentileSeries(), plotPercentiles(), plotRaw(), plotSubset()

Examples

# For traditional continuous norming model
result <- cnorm(raw = elfe$raw, group = elfe$group)
plotDerivative(result, minAge=2, maxAge=5, stepAge=.2, minNorm=25, maxNorm=75, stepNorm=1)

cNORM documentation built on Nov. 4, 2024, 5:07 p.m.