plotRaw

The function plots the raw data against the fitted scores from
the regression model per group. This helps to inspect the precision
of the modeling process. The scores should not deviate too far from
regression line.

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 

plotRaw function

<dl><dt>data</dt>
<dd>The raw data within a data.frame or cnorm object</dd>
<dt>model</dt>
<dd>The regression model (optional)</dd>
<dt>group</dt>
<dd>The grouping variable</dd>
<dt>raw</dt>
<dd>The raw score variable</dd>
<dt>type</dt>
<dd>Type of display: 0 = plot manifest against fitted values, 1 = plot
manifest against difference values</dd></dl>

Arguments

Plot manifest and fitted raw scores — plotRaw

<dl>

<dt>data</dt>
<dd>The raw data within a data.frame or cnorm object</dd>


<dt>model</dt>
<dd>The regression model (optional)</dd>


<dt>group</dt>
<dd>The grouping variable</dd>


<dt>raw</dt>
<dd>The raw score variable</dd>


<dt>type</dt>
<dd>Type of display: 0 = plot manifest against fitted values, 1 = plot
manifest against difference values</dd>

</dl>

plotRaw: Plot manifest and fitted raw scores

Description

Usage

Arguments

See Also

Examples