Malaria parasite clearance rate regression: an R software package for a Bayesian hierarchical regression model
Saeed Sharifi-Malvajerdi, Feiyu Zhu, Colin B Fogarty, Michael P Fay, Rick M Fairhurst, Jennifer A Flegg, Kasia Stepniewska, Dylan S Small
MALARIA JOURNAL | BMC | Published : 2019
BACKGROUND: Emerging resistance to anti-malarial drugs has led malaria researchers to investigate what covariates (parasite and host factors) are associated with resistance. In this regard, investigation of how covariates impact malaria parasites clearance is often performed using a two-stage approach in which the WWARN Parasite Clearance Estimator or PCE is used to estimate parasite clearance rates and then the estimated parasite clearance is regressed on the covariates. However, the recently developed Bayesian Clearance Estimator instead leads to more accurate results for hierarchial regression modelling which motivated the authors to implement the method as an R package, called "bhrcr". M..View full abstract
This research was supported in part by the Intramural Research Program of the NIH, NIAID.