plotDensity

The function plots the density curves based on the regression model against
the actual percentiles from the raw data. As in 'plotNormCurves',
please check for inconsistent curves, especially curves showing implausible shapes as f. e.
violations of biuniqueness.

Conventional methods for producing standard scores or percentiles
in psychometrics or biometrics are often plagued with 'jumps' or 'gaps'
(i.e., discontinuities) in norm tables and low confidence for assessing
extreme scores. The continuous norming method introduced by A. Lenhard et al.
(2016, <doi:10.1177/1073191116656437>; 2019, <doi:10.1371/journal.pone.0222279>;
2021 <doi: 10.1177/0013164420928457>) estimates percentile development
(e. g. over age) and generates continuous test norm scores on the basis of
the raw data from standardization samples, without requiring assumptions
about the distribution of the raw data: Norm scores are directly established
from raw data by modeling the latter ones as a function of both percentile
scores and an explanatory variable (e.g., age). The method minimizes bias
arising from sampling and measurement error, while handling marked deviations
from normality, addressing bottom or ceiling effects and capturing almost
all of the variance in the original norm data sample. It includes procedures
for post stratification of norm samples to overcome bias in data collection
and to mitigate violations of representativeness. An online demonstration is
available via <https://cnorm.shinyapps.io/cNORM/>.

Wolfgang Lenhard

cNORM

Continuous Norming

Alexandra Lenhard

Sebastian Gary

WPS publisher 

plotDensity function

<dl><dt>model</dt>
<dd>The model from the bestModel function or a cnorm object</dd>
<dt>minRaw</dt>
<dd>Lower bound of the raw score</dd>
<dt>maxRaw</dt>
<dd>Upper bound of the raw score</dd>
<dt>minNorm</dt>
<dd>Lower bound of the norm score</dd>
<dt>maxNorm</dt>
<dd>Upper bound of the norm score</dd>
<dt>group</dt>
<dd>Column of groups to plot</dd>
<dt>covariate</dt>
<dd>In case, a covariate has been used, please specify the degree of the covariate /
the specific value here.</dd></dl>

Arguments

Plot the density function per group by raw score — plotDensity

<dl>

<dt>model</dt>
<dd>The model from the bestModel function or a cnorm object</dd>


<dt>minRaw</dt>
<dd>Lower bound of the raw score</dd>


<dt>maxRaw</dt>
<dd>Upper bound of the raw score</dd>


<dt>minNorm</dt>
<dd>Lower bound of the norm score</dd>


<dt>maxNorm</dt>
<dd>Upper bound of the norm score</dd>


<dt>group</dt>
<dd>Column of groups to plot</dd>


<dt>covariate</dt>
<dd>In case, a covariate has been used, please specify the degree of the covariate /
the specific value here.</dd>

</dl>

plotDensity: Plot the density function per group by raw score

Description

Usage

Arguments

See Also

Examples