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Lgpr: An interpretable nonparametric method for inferring covariate effects from longitudinal Data
1 month ago - By Oxford Journals
AbstractMotivationLongitudinal study designs are indispensable for studying disease progression. Inferring covariate effects from longitudinal data, however, requires interpretable methods that can model complicated covariance structures and detect nonlinear effects of both categorical and continuous covariates, as well as their interactions. Detecting disease effects is hindered by the fact that they often occur rapidly near the disease initiation time, and this time point cannot be exactly observed. An additional challenge is that the effect magnitude can be heterogeneous over the...
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2nd International Conference on Generic Drugs and Biosimilars
2nd International Conference on Generic Drugs and Biosimilars
2nd International Conference on Generic Drugs and Biosimilars
2nd International Conference on Generic Drugs and Biosimilars
Three-layered Masks Most Effective Against Large Respiratory Droplets
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