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Multivariate linear mixed models (mvLMMs) are powerful tools for testing associations between single-nucleotide polymorphisms and multiple correlated phenotypes while controlling for population ...

When two binary responses are measured for each study subject across time, it may be of interest to model how the bivariate associations and marginal univariate risks involving the two responses ...

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision ...

Papers in this series provide tutorials on statistical methods that are used in precision oncology, such as methods in discovery phase, diagnostics, and drug development. The goal of the series is to ...