Fit-hacking: Questionable research practices in structural equation modeling

Abstract Structural equation modeling (SEM) is a powerful and flexible modeling framework for testing complex relationships among observed and latent variables. However, its methodological complexity and analytical flexibility also increase the risk of questionable research practices (QRPs), especially in fields like applied linguistics, where training in advanced statistics may be limited. This article synthesizes the literature on QRPs and applies it to SEM by identifying seven categories of problematic practices: not checking assumptions, not validating a measurement model, not testing competing models, not sufficiently justifying modeling decisions, relying on post hoc model modification, overemphasizing global fit indices, and incomplete or nontransparent reporting. Each practice is described with examples and linked to broader issues in research ethics and transparency. The paper concludes with concrete recommendations for improving the credibility and reproducibility of SEM research, emphasizing the integration of best practices with the principles of open science.