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Updated: Apr 17, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Accurate liability estimation improves power in ascertained case-control studies
Omer Weissbrod1, Christoph Lippert2, Dan Geiger1
1Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel.
Abstract:
Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in nonrandomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (liability estimator as a phenotype; https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and we demonstrate that this can lead to a substantial power increase.
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