betaNormTable

This function generates a table of beta-binomial distribution properties (cumulative probabilities,
density, percentiles, and z-scores) for a specified group, using alpha (`a`) and beta (`b`) parameters
predicted by a model created with the `betaContinuous` function.

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 

betaNormTable function

<dl><dt>model</dt>
<dd>A list containing the components from a `betaContinuous` model output.</dd>
<dt>group</dt>
<dd>A number specifying the group variable for which predictions and
subsequent beta-binomial distribution calculations are desired.</dd>
<dt>m</dt>
<dd>An optional stop criterion in table generation. Positive integer lower than n</dd></dl>

Arguments

Generate norm table from parametric continuous norming with Beta-Binomial Parameters — betaNormTable

<dl>

<dt>model</dt>
<dd>A list containing the components from a `betaContinuous` model output.</dd>


<dt>group</dt>
<dd>A number specifying the group variable for which predictions and
subsequent beta-binomial distribution calculations are desired.</dd>


<dt>m</dt>
<dd>An optional stop criterion in table generation. Positive integer lower than n</dd>

</dl>

betaNormTable: Generate norm table from parametric continuous norming with Beta-Binomial Parameters

Description

Usage

Value

Arguments

Examples