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stat.ME2025

Addressing zero-inflated and mis-measured functional predictors in scalar-on-function regression model

Heyang Ji, Lan Xue, Ufuk Beyaztas +4

Wearable devices are often used in clinical and epidemiological studies to monitor physical activity behavior and its influence on health outcomes. These devices are worn over mult…

stat.ME2025

MECfda: An R Package for Bias Correction Due to Measurement Error in Functional and Scalar Covariates in Scalar-on-Function Regression Models

Heyang Ji, Ufuk Beyaztas, Nicolas Escobar-Velasquez +6

Functional data analysis (FDA) deals with high-resolution data recorded over a continuum, such as time, space or frequency. Device-based assessments of physical activity or sleep a…

stat.ME2025

Least squares-based methods to bias adjustment in scalar-on-function regression model using a functional instrumental variable

Xiwei Chen, Ufuk Beyaztas, Caihong Qin +5

Instrumental variables are widely used to adjust for measurement error bias when assessing associations of health outcomes with ME prone independent variables. IV approaches addres…

stat.ME2025

Clustering of functional data prone to complex heteroscedastic measurement error

Andi Mai, Lan Xue, Roger Zoh +1

Several factors make clustering of functional data challenging, including the infinite-dimensional space to which observations belong and the lack of a defined probability density…

stat.ME2025

Functional Linear Cox Regression Model with Frailty

Deniz Inan, Ufuk Beyaztas, Carmen D. Tekwe +2

This paper presents a functional linear Cox regression model with frailty to tackle unobserved heterogeneity in survival data with functional covariates. While traditional Cox mode…