Abstract
Researchers assessing psychological constructs have to understand and choose between several competing measures. Item Pool Visualization (IPV, Dantlgraber et al., 2019) was developed to offer a systematic and detailed portrayal of the actual
content and internal balance of competing measures. To enable the use of IPV, we developed and present here the IPV R package. Its aim is to allow researchers to add IPV to their repertoire with minimal effort. Creating IPV charts from raw data requires two simple function calls, because the package streamlines model specification, model estimation, and chart creation. It improves IPV conceptually by introducing the aggregate center distance and the item overview chart. It provides
many customization options and generates high-quality, vector-based PDF output. The workflow of the package is explained using a reproducible open data example from a personality assessment.
content and internal balance of competing measures. To enable the use of IPV, we developed and present here the IPV R package. Its aim is to allow researchers to add IPV to their repertoire with minimal effort. Creating IPV charts from raw data requires two simple function calls, because the package streamlines model specification, model estimation, and chart creation. It improves IPV conceptually by introducing the aggregate center distance and the item overview chart. It provides
many customization options and generates high-quality, vector-based PDF output. The workflow of the package is explained using a reproducible open data example from a personality assessment.
| Original language | American English |
|---|---|
| Journal | Behavior Research Methods |
| Publication status | Published - 7 Feb 2023 |