
Abstract We provide an overview of and guidance for applying exploratory bifactor models to vocational research. First, we describe bifactor models and highlight their potential and actual applications in vocational psychology. Second, we review the theoretical bases of bifactor models and offer methodological guidance to correctly implement and interpret these models in practice. Third, we estimate a bifactor model in two vocational datasets to illustrate the concepts reviewed in this manuscript. The resulting models highlight novel insights in careers research (e.g., developmental performance feedback and personality [conscientiousness] modeling) that are made possible by leveraging bifactor measurement models. Overall, this manuscript provides a useful introduction to bifactor models to facilitate vocational behavior scholars and practitioners in thoughtfully producing and consuming bifactor models in their own research.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 14 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
