17 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…
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…
Estimating the effect of lymphovascular invasion on 2-year survival probability under endogeneity: a recursive copula-based approach
Yang Ou, Lan Xue, Carmen Tekwe +2
Lymphovascular invasion (LVI) is an important prognostic marker for head and neck squamous cell carcinoma (HNSC), but the true effect of LVI on survival may be distorted by endogen…
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…
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…
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…
Spatial function-on-function regression
Ufuk Beyaztas, Han Lin Shang, Gizel Bakicierler Sezer +3
We introduce a spatial function-on-function regression model to capture spatial dependencies in functional data by integrating spatial autoregressive techniques with functional pri…
Clustering functional data with measurement errors: a simulation-based approach
Tingyu Zhu, Lan Xue, Carmen Tekwe +3
Clustering analysis of functional data, which comprises observations that evolve continuously over time or space, has gained increasing attention across various scientific discipli…
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…
Generalized functional linear regression models with a mixture of complex function-valued and scalar-valued covariates prone to measurement error
Yuanyuan Luan, Roger S. Zoh, Sneha Jadhav +2
While extensive work has been done to correct for biases due to measurement error in scalar-valued covariates prone to errors in generalized linear regression models, limited work…
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…
A Bayesian Semi-Parametric Scalar-On-Function Quantile Regression with Measurement Error using the GAL
Roger S. Zoh, Annie Yu, Carmen Tekwe
Quantile regression provides a consistent approach to investigating the association between covariates and various aspects of the distribution of the response beyond the mean. When…
A fully Bayesian semi-parametric scalar-on-function regression (SoFR) with measurement error using instrumental variables
Roger S. Zoh, Yuanyuan Luan, Carmen Tekwe
Wearable devices such as the ActiGraph are now commonly used in health studies to monitor or track physical activity. This trend aligns well with the growing need to accurately ass…
An approximate Bayes factor based high dimensional MANOVA using Random Projections
Roger S Zoh, Fangzheng Xie
High-dimensional mean vector testing problem for two or more groups remain a very active research area. In these setting, traditional tests are not applicable because they involve…