5 papers
Variable Selection for Fixed and Random Effects in Multilevel Functional Mixed Effects Models
Rahul Ghosal, Marcos Matabuena, Enakshi Saha
We develop a new method for simultaneously selecting fixed and random effects in a multilevel functional regression model. The proposed method is motivated by accelerometer-derived…
ROC Analysis with Covariate Adjustment Using Neural Network Models: Evaluating the Role of Age in the Physical Activity-Mortality Association
Ziad Akram Ali Hammouri, Yating Zou, Rahul Ghosal +2
The receiver operating characteristic (ROC) curve and its summary measure, the Area Under the Curve (AUC), are well-established tools for evaluating the efficacy of biomarkers in b…
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi +2
Depth measures are powerful tools for defining level sets in emerging, non--standard, and complex random objects such as high-dimensional multivariate data, functional data, and ra…
Variable Selection in Functional Linear Cox Model
Yuanzhen Yue, Stella Self, Yichao Wu +2
Modern biomedical studies frequently collect complex, high-dimensional physiological signals using wearables and sensors along with time-to-event outcomes, making efficient variabl…
Screening for Diabetes Mellitus in the U.S. Population Using Neural Network Models and Complex Survey Designs
Marcos Matabuena, Juan C. Vidal, Rahul Ghosal +1
Complex survey designs are commonly employed in many medical cohorts. In such scenarios, developing case-specific predictive risk score models that reflect the unique characteristi…