5 papers
A Bayesian Functional Accelerated Failure-Time Model with Varying Effects Correcting for Measurement Error
Joseph Yang, Roger Zoh, Carmen Tekwe +1
Functional data collected as continuously observed trajectories arise naturally in many biomedical settings, and a key inferential goal is understanding how such functional covaria…
Correcting Measurement Error and Zero Inflation in Functional Covariates for Scalar-on-Function Quantile Regression
Caihong Qin, Lan Xue, Ufuk Beyaztas +4
Wearable devices collect time-varying biobehavioral data, offering opportunities to investigate how behaviors influence health outcomes. However, these data often contain measureme…
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…
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…
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…