Model-based incremental validity

As an important facet of construct validity, incremental validity has been the focus of many applied investigations across a wide array of disciplines. Unfortunately, traditional methodological approaches for studying incremental validity, typically rooted in multiple regression, have many limitations that can hinder such assessments. In the current work, a strategy based in structural equation modeling is offered that greatly expands researchers' ability to investigate incremental validity of multiple individual predictors or blocks of predictors all within a single structural model. Models for four different research scenarios are presented, where the predictors of focal interest are: (a) individual measured predictors, (b) individual latent predictors, (c) blocks of measured predictors, and (d) blocks of latent predictors. Technical details of model specifications and model constraints are provided, and flexible extensions to other interesting questions (e.g., comparisons across populations) are discussed. Two empirical examples are included to illustrate the application of the proposed methods in different applied settings; complete Mplus and R syntax for both illustrative examples is supplied. (PsycInfo Database Record (c) 2023 APA, all rights reserved).