4 papers
Inferential Validity of Digital Health Measures
Carmen D. Tekwe, Mercy Oladuti, Yuanyuan Luan +5
Digital health measures increasingly inform treatment evaluation, risk classification, clinical monitoring, and regulatory decisions. Existing validity concepts concern a measure's…
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…
Scalable regression calibration approaches to correcting measurement error in multi-level generalized functional linear regression models with heteroscedastic measurement errors
Yuanyuan Luan, Roger S. Zoh, Erjia Cui +3
Wearable devices permit the continuous monitoring of biological processes, such as blood glucose metabolism, and behavior, such as sleep quality and physical activity. The continuo…
Adjusting for bias due to measurement error in functional quantile regression models with error-prone functional and scalar covariates
Xiwei Chen, Yuanyuan Luan, Roger S. Zoh +3
Wearable devices enable the continuous monitoring of physical activity (PA) but generate complex functional data with poorly characterized errors. Most work on functional data view…