Simulation study evaluates confidence intervals and robustness in structural equation modelling, highlighting differences in effectiveness.
Likelihood-based confidence intervals often perform better than Wald-based intervals instructural equation modelling, but one challenge involves their robustness to distributionalassumption violations. While Falk (2018) implemented a “robust” variant based on invertinga test by Satorra (2000), other scaled difference tests are available. These approaches havenot been compared to Wald-based intervals based on a sandwich covariance matrix withobserved information (Huber-White or “MLR”). In addition, lavaan-based softwareimplementations are challenging and several solutions, including the new semlbci package(Cheung & Pesigan, 2023), have not been compared. We report two simulations evaluatingthree scaled difference tests, Huber-White standard errors, and two softwareimplementations. Under several nonnormality conditions, we examine a classic behavioralgenetics model and a cross-lagged panel model with an indirect effect. Satorra’s (2000)difference test worked best and sometimes outperformed Huber-White standard errors. Wedocument challenges in estimation of these intervals if lavaan (Rosseel, 2012) is used.
No takes yet. Share an insight, caveat, or question.
Falk et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: