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Personalized medicine allows individuals to choose the best fit of their treatments based on their characteristics through an individualized treatment regime. In this paper, we develop a pool adjacent violators algorithm–assisted learning method to find the optimal individualized treatment regime under the monotone single‐index outcome gain model. The proposed estimator is more efficient than peers,...
In this paper, we propose a semiparametric regression model that is built upon an isotonic regression model with the assumption that the random error follows a skewed distribution. We develop an expectation‐maximization algorithm for obtaining the maximum likelihood estimates of the model parameters, examine the asymptotic properties of the estimators, conduct simulation studies to explore the performance...
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