Research Projects

Confounder-adjusted Outcome-guided dimension Reduction and Discriminant Effect size

Logistic regression is widely used for binary outcomes but struggles with perfect separation, causing inflated odds ratios and unstable predictions. We propose a pre-hoc method to detect both direct and latent perfect separation and show that although latent separation leads to infinite estimates, the ratio of coefficients converges to a true value.

The project focus on explore the concordance of 16S rRNA and shotgun metagenome sequencing data from different perspectives.

There is a pressing need for early diagnosis and novel therapies to address the growing incidence of age-related conditions such as Alzheimer’s disease (AD) and dementia.

The project focus on explore the concordance of 16S rRNA and shotgun metagenome sequencing data from different perspectives.

In this study, we focus on the primary outcomes of NCI and aim to enhance our understanding and knowledge of it and identify associated potential risk factors including metabolic-related markers or inflammatory factors by leveraging the highly correlated information from secondary outcomes of frailty, falls and disability.