  Linear mixed models (LMMs) have emerged as the method of choice for
confounded genome-wide association studies. However, the performance of LMMs in
non-randomly 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 demonstrate
that this can lead to a substantial power increase.
