VARIANCE FUNCTIONS AND THE MINIMUM DETECTABLE CONCENTRATION IN ASSAYS
成果类型：
Article
署名作者：
DAVIDIAN, M; CARROLL, RJ; SMITH, W
署名单位：
Texas A&M University System; Texas A&M University College Station; Eli Lilly; Lilly Research Laboratories; Eli Lilly; Lilly Research Laboratories
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/75.3.549
发表日期：
1988
页码：
549556
关键词：
摘要：
Assay data are often fitted by a nonlinear heteroscedastic regression model with the standard deviation of the response typically taken to be proportional to a power .theta. of the mean. For many assays, how one estimates .theta. does not greatly affect estimates of the mean regression function. Assay analysis also involves estimation of auxiliary calibration constructs such as minimum detectable concentration. An asymptotic theory is developed to show that standard methods for estimating .theta. lead to estimators for minimum detectable concentration that can differ markedly in efficiency. Stimulation results support the asymptotic theory.