Results 41 to 50 of about 838,163 (294)
Covariate Assisted Principal Regression for Covariance Matrix Outcomes [PDF]
Biostatistics, 2018 Abstract Modeling variances in data has been an important topic in many fields, including in financial and neuroimaging analysis. We consider the problem of regressing covariance matrices on a vector covariates, collected from each observational unit. The main aim is to uncover the variation in the covariance matrices
Zhao, Yi +4 more
openaire +2 more sources
Sensitivity models for missing covariates in the analysis of survival data from multiple surveys [PDF]
, 2007 Using individual patient data from five independent surveys, we evaluate regional variations in survival in cerebral palsy. The influence of four important variables measuring disability, which are only partially observed for many cases, are analysed ...
Hemming, Karla, Hutton, Jane
core
tonyewong/covariates: Codes for ASCMO article
, 2018 <p><strong>An Integration and Assessment of Multiple Covariates of Nonstationary Storm Surge Statistical Behavior by Bayesian Model Averaging</strong></p> <p>These are the data, modeling and analysis codes for the project ...
Tony Wong
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Outcomes in relapsed or refractory pediatric and AYA bone sarcomas remain poor, and the impact of early referral to specialized sarcoma centers on survival is unclear. Early centralization of care may improve local and systemic treatment quality, but evidence in this population is limited.
Justyna Antoniuk‐Majchrzak +9 more
wiley +1 more source
Is Gender an Important Factor in the Precision Medicine Approach to Levocetirizine?
PharmaceuticsCurrently, there is insufficient information on the variability in levocetirizine pharmacometrics among individuals, a crucial aspect for establishing its clinical use.
Seung-Hyun Jeong +2 more
doaj +1 more source
Robust Sales forecasting Using Deep Learning with Static and Dynamic Covariates
Applied System Innovation, 2023 Retailers must have accurate sales forecasts to efficiently and effectively operate their businesses and remain competitive in the marketplace. Global forecasting models like RNNs can be a powerful tool for forecasting in retail settings, where multiple ...
Patrícia Ramos, José Manuel Oliveira
doaj +1 more source
Spectral Ranking with Covariates
, 2023 We consider spectral approaches to the problem of ranking n players given their incomplete and noisy pairwise comparisons, but revisit this classical problem in light of player covariate information. We propose three spectral ranking methods that incorporate player covariates and are based on seriation, low-rank structure assumption and canonical ...
Siu Lun Chau +2 more
openaire +2 more sources
Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study [PDF]
, 2010 Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the ...
Holder, Roger +15 more
core +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction Peritoneal dialysis (PD) is an established home‐based kidney replacement therapy (KRT), but its uptake remains low in Japan. We evaluated whether individualized education in a dedicated outpatient clinic was associated with the initiation of PD.
Yasuko Ito +7 more
wiley +1 more source
A Multiple Imputation Workflow for Handling Missing Covariate Data in Pharmacometrics Modeling
CPT: Pharmacometrics & Systems PharmacologyCovariate missingness is a prevalent issue in pharmacometrics modeling. Incorrect handling of missing covariates can lead to biased parameter estimates, adversely affecting clinical practice and drug development dosing decisions.
My‐Luong Vuong +2 more
doaj +1 more source