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The existing methods for subgroup analysis can be roughly divided into two categories: finite mixture models (FMM) and regularization methods with an ℓ1‐type penalty. In this paper, by introducing the group centers and ℓ2‐type penalty in the loss function, we propose a novel center‐augmented regularization (CAR) method; this method can be regarded as a unification of the regularization method and...
Semicompeting risk outcome data (e.g., time to disease progression and time to death) are commonly collected in clinical trials. However, analysis of these data is often hampered by a scarcity of available statistical tools. As such, we propose a novel semiparametric transformation model that improves the existing models in the following two ways. First, it estimates regression coefficients and association...
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