Multiple-component radiation-measurement error models.
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.
Burr
T L
TL
Statistical Science Group, Mail Stop F600, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. tburr@lanl.gov
Hemphill
G S
GS
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
D011868:Radioisotopes