4 papers
Representation Learning for Semiparametric Causal Mediation Analysis under No Essential Heterogeneity
Roberto Faleh, Sofia Morelli, Holger Brandt
We propose a two-stage estimator for structural mediation parameters that combines deep representation learning with G-estimation under the "no essential heterogeneity" (NEH) assum…
RAPSEM: Identifying Latent Mediators Without Sequential Ignorability via a Rank-Preserving Structural Equation Model
Sofia Morelli, Roberto Faleh, Holger Brandt
Standard structural equation models (SEMs) are often used to identify latent mediators. However, valid inference typically relies on the strong, frequently violated Sequential Igno…
Dynamic Latent Class Structural Equation Modeling: A Hands-On Tutorial for Modeling Intensive Longitudinal Data
Roberto Faleh, Sofia Morelli, Vivato Andriamiarana +3
In this tutorial, we provide a hands-on guideline on how to implement complex Dynamic Latent Class Structural Equation Models (DLCSEM) in the Bayesian software JAGS. We provide bui…
Advantages and limitations in the use of transfer learning for individual treatment effects in causal machine learning
Seyda Betul Aydin, Holger Brandt
Generalizing causal knowledge across diverse environments is challenging, especially when estimates from large-scale datasets must be applied to smaller or systematically different…