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).
Returns
A ggplot object representing the derivative of the regression function.
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.
Note
This function is currently incompatible with reversed raw score scales ('descent' option).
Examples
# For traditional continuous norming modelresult <- cnorm(raw = elfe$raw, group = elfe$group)plotDerivative(result, minAge=2, maxAge=5, stepAge=.2, minNorm=25, maxNorm=75, stepNorm=1)