title: Multiple-component radiation-measurement error models.
abstract: Measurement error modeling and assessment are crucial to any assay method. Realistic error models prioritize future efforts to reduce key error components and provide a way to estimate total ("random" and "systematic") measurement error. This paper describes multiple-component error models for radiation-based assay, gives example applications, and describes strategies for choosing and then fitting error models.
authors.affiliation: Statistical Science Group, Mail Stop F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. tburr@lanl.gov
authors.forename: T L
authors.initials: TL
authors.lastname: Burr
authors.forename: G S
authors.initials: GS
authors.lastname: Hemphill
mesh_terms: D003627:Data Interpretation, Statistical; D008956:Models, Chemical; D015233:Models, Statistical; D011829:Radiation Dosage; D011868:Radioisotopes / Q000032:analysis*; D011874:Radiometry / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D011868:Radioisotopes