10 papers
Sparse Longitudinal Functional Principal Component Analysis for Episodic Ambulatory Behavioral Assessments
Nidhi Pai, Yu Fang, Srijan Sen +2
Accurately monitoring mental fatigue is critical for improving workplace safety and productivity. A recent study examined unobtrusively collected smartphone typing speed as a poten…
PCA score regression: the art of losing power
Yu Lu, Nidhi Pai, Erjia Cui +1
The regression of principal component scores (RPCS) on covariates is a widely used analytic approach to detect and test for associations between functional measurements and study p…
Quantifying Time-Varying Physical Activity Intervention Effects via Functional Regression
Nidhi Pai, Yu Lu, Kristin A. Linn +1
Physical activity (PA) intervention studies often collect repeated intensity measurements over long observation periods. Quantifying the variation in intervention effects over the…
BAMIFun: Bayesian Multiple Imputation for Functional Data
Ziren Jiang, Lei Xuan, Eric F. Lock +1
Missing data are pervasive in modern functional datasets, where trajectories are often sparsely or irregularly observed. Although Functional Principal Component Analysis (FPCA) is…
Inference for the Extended Functional Cox Model: A UK Biobank Case Study
Erjia Cui, Angela Zhao, Ciprian M. Crainiceanu
Multiple studies have shown that scalar summaries of objectively measured physical activity (PA) using accelerometers are the strongest predictors of mortality, outperforming all t…
Fast Penalized Generalized Estimating Equations for Large Longitudinal Functional Datasets
Gabriel Loewinger, Alex W. Levis, Erjia Cui +1
Longitudinal binary or count functional data are common in neuroscience, but are often too large to analyze with existing functional regression methods. We propose one-step penaliz…
Generalized Conditional Functional Principal Component Analysis
Yu Lu, Xinkai Zhou, Erjia Cui +4
We propose generalized conditional functional principal components analysis (GC-FPCA) for the joint modeling of the fixed and random effects of non-Gaussian functional outcomes. Th…
Continuous-time multivariate analysis
Biplab Paul, Philip T. Reiss, Erjia Cui +1
The starting point for much of multivariate analysis (MVA) is an data matrix whose rows represent observations and whose columns represent variables. Some multi…
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 case study of glucose levels during sleep using fast function on scalar regression inference
Renat Sergazinov, Andrew Leroux, Erjia Cui +4
Continuous glucose monitors (CGMs) are increasingly used to measure blood glucose levels and provide information about the treatment and management of diabetes. Our motivating stud…