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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.11063 |
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Table of Contents:
- Structural Equation Modeling (SEM) is a flexible statistical technique with multiple applications, including behavioral genetics and social sciences. Building on the original design of the umx package, which improved accessibility to OpenMx by specifying a concise syntax, umx v4.5 extends functionality for longitudinal and causal twin designs while improving interoperability with graphical modelling tools such as Onyx. New capabilities include: classic and modern cross-lagged panel models; Mendelian Randomization Direction-of-Causation (MR-DoC) twin models incorporating polygenic scores as instruments; support for definition variables directly in umxRAM(); a workflow for importing paths from Ωnyx; a dedicated function for incorporating censored variables' data into models, particularly valuable in biomarker research; improved covariate placeholder handling for definition variables; sex-limitation modelling across five twin groups, accommodating quantitative and qualitative sex differences; and covariate residualization in wide- or long-format data. These new functionalities accelerate reproducible, reliable, publication-ready twin and family modelling, and integrated journal-quality reporting, thereby lowering barriers to genetic epidemiological analyzes.