Objectives This study uses nationally representative survey data from the USA to estimate the relationship between a history of heart attack or stroke with the prevalence of mental health symptoms.

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering ...

Specifically, we introduce Diffusion Gated Linear Attention Transformers (DiG), a simple, adoptable solution with minimal parameter overhead. We offer two variants, i,e, a plain and U-shape ...

Our findings indicate that US adult baseline contact patterns show little variability over time after controlling for disease ...

We consider the shuffled linear regression problem where the correspondences between covariates and responses are unknown. While the existing formulation assumes an ideal underlying bijection in which ...

Abstract: We consider the problem of estimating self-exciting generalized linear models from limited binary observations, where the history of the process serves as the covariate. We analyze the ...

All available studies were included in the primary meta-analysis regardless of missing covariate data. For the meta-regression models, only studies with complete information on all four modifiers were ...

Compared to logistic regression, linear regression better describes the association between two continuous variables while controlling for other confounding factors, but in the case of nonlinear ...