| Literature DB >> 28737413 |
Tobias Koch1, Jana Holtmann2, Johannes Bohn2, Michael Eid2.
Abstract
An increasing number of psychological studies are devoted to the analysis of g-factor structures. One key purpose of applying g-factor models is to identify predictors or potential causes of the general and specific effects. Typically, researchers relate predictor variables directly to the general and specific factors using a classical mimic approach. However, this procedure bears some methodological challenges, which often lead to model misspecification and biased parameter estimates. We propose 2 possible modeling strategies to circumvent these problems: the multiconstruct bifactor and the residual approach. We illustrate both modeling approaches for the application of g-factor models to longitudinal and multitrait-multimethod data. Practical guidelines are provided for choosing an appropriate method in empirical applications, and the implications of this investigation for multimethod and longitudinal research are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).Mesh:
Year: 2017 PMID: 28737413 DOI: 10.1037/met0000146
Source DB: PubMed Journal: Psychol Methods ISSN: 1082-989X