| Autor: |
Bliese PD; Management Department., Maltarich MA; Management Department., Hendricks JL; Management Department., Hofmann DA; Kenan-Flagler Business School, The University of North Carolina at Chapel Hill., Adler AB; Walter Reed Army Institute of Research. |
| Jazyk: |
angličtina |
| Zdroj: |
The Journal of applied psychology [J Appl Psychol] 2019 Feb; Vol. 104 (2), pp. 293-302. Date of Electronic Publication: 2018 Sep 17. |
| DOI: |
10.1037/apl0000349 |
| Abstrakt: |
The ability to detect differences between groups partially impacts how useful a group-level variable will be for subsequent analyses. Direct consensus and referent-shift consensus group-level constructs are often measured by aggregating group member responses to multi-item scales. We show that current measurement validation practice for these group-level constructs may not be optimized with respect to differentiating groups. More specifically, a 10-year review of multilevel articles in top journals reveals that multilevel measurement validation primarily relies on procedures designed for individual-level constructs. These procedures likely miss important information about how well each specific scale item differentiates between groups. We propose that group-level measurement validation be augmented with information about each scale item's ability to differentiate groups. Using previously published datasets, we demonstrate how ICC(1) estimates for each item of a scale provide unique information and can produce group-level scales with higher ICC(1) values that enhance predictive validity. We recommend that researchers supplement conventional measurement validation information with information about item-level ICC(1) values when developing or modifying scales to assess group-level constructs. (PsycINFO Database Record (c) 2019 APA, all rights reserved). |
| Databáze: |
MEDLINE |
| Externí odkaz: |
|
