derive

Calculates the derivative of the location / norm value from the regression model with the first
derivative as the default. This is useful for finding violations of model assumptions and problematic
distribution features as f. e. bottom and ceiling effects, non-progressive norm scores within an
age group or in general #' intersecting percentile curves.

A comprehensive toolkit for generating continuous test norms in
psychometrics and biometrics, and analyzing model fit. The package offers both
distribution-free modeling using Taylor polynomials and parametric modeling
using the beta-binomial distribution. Originally developed for achievement
tests, it is applicable to a wide range of mental, physical, or other test
scores dependent on continuous or discrete explanatory variables. The package
provides several advantages: It minimizes deviations from representativeness
in subsamples, interpolates between discrete levels of explanatory variables,
and significantly reduces the required sample size compared to conventional
norming per age group. cNORM enables graphical and analytical evaluation of
model fit, accommodates a wide range of scales including those with negative
and descending values, and even supports conventional norming. It generates
norm tables including confidence intervals. It also includes methods for
addressing representativeness issues through Iterative Proportional Fitting.

Wolfgang Lenhard

cNORM

Continuous Norming

Alexandra Lenhard

Sebastian Gary

WPS publisher 

derive function

<dl><dt>model</dt>
<dd>The regression model or a cnorm object</dd>
<dt>order</dt>
<dd>The degree of the derivate, default: 1</dd></dl>

Arguments

Derivative of regression model — derive

<dl>

<dt>model</dt>
<dd>The regression model or a cnorm object</dd>


<dt>order</dt>
<dd>The degree of the derivate, default: 1</dd>

</dl>

derive: Derivative of regression model

Description

Usage

Value

Arguments

See Also

Examples