printSubset

After conducting the model fitting procedure on the data set, the best fitting
model has to be chosen. The print function shows the R2 and other information
on the different best fitting models with increasing number of predictors.

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 

printSubset function

<dl><dt>x</dt>
<dd>The model from the 'bestModel' function or a cnorm object</dd>
<dt>...</dt>
<dd>additional parameters</dd></dl>

Arguments

Convenience method for printing model selection information — printSubset

<dl>

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


<dt>...</dt>
<dd>additional parameters</dd>

</dl>

printSubset: Convenience method for printing model selection information

Description

Usage

Value

Arguments

See Also

Examples