ratings_missing

A simulated dataset with 350 cases judged by 5 judges, using a planned missingness design.

datasets

Psychometric analysis and scoring of judgment data using polytomous Item-Response Theory (IRT) models, as described in Myszkowski and Storme (2019) <doi:10.1037/aca0000225> and Myszkowski (2021) <doi:10.1037/aca0000287>. A function is used to automatically compare and select models, as well as to present a variety of model-based statistics. Plotting functions are used to present category curves, as well as information, reliability and standard error functions.

Nils Myszkowski

Item Response Theory Modeling and Scoring for Judgment Data

ratings_missing function

A data.frame with 350 rows (cases) and 5 columns (judges):<dl>
 <dt>Judge_1</dt>
<dd>Judgments of judge 1</dd> <dt>Judge_2</dt>
<dd>Judgments of judge 2</dd> <dt>Judge_3</dt>
<dd>Judgments of judge 3</dd> <dt>Judge_4</dt>
<dd>Judgments of judge 4</dd> <dt>Judge_5</dt>
<dd>Judgments of judge 5</dd>
</dl>

Format

A simulated dataset with 350 cases judged by 5 judges, using a planned missingness design. — ratings_missing

A data.frame with 350 rows (cases) and 5 columns (judges):<dl>
 <dt>Judge_1</dt>
<dd>Judgments of judge 1</dd>

 <dt>Judge_2</dt>
<dd>Judgments of judge 2</dd>

 <dt>Judge_3</dt>
<dd>Judgments of judge 3</dd>

 <dt>Judge_4</dt>
<dd>Judgments of judge 4</dd>

 <dt>Judge_5</dt>
<dd>Judgments of judge 5</dd>


</dl>

ratings_missing: A simulated dataset with 350 cases judged by 5 judges, using a planned missingness design.

Description

Usage

Arguments

Format