VARIANCE FUNCTIONS AND THE MINIMUM DETECTABLE CONCENTRATION IN ASSAYS

abstract

• 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 of the mean. For many assays, how one estimates 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 lead to estimators for minimum detectable concentration that can differ markedly in efficiency. Simulation results support the asymptotic theory. 1988 Biometrika Trust.

authors

• Carroll, Raymond

published proceedings

• BIOMETRIKA

altmetric score

• 3

author list (cited authors)

• DAVIDIAN, M., CARROLL, R. J., & SMITH, W.

citation count

• 67

complete list of authors

• DAVIDIAN, M||CARROLL, RJ||SMITH, W

publication date

• September 1988

publisher

• Oxford University Press (OUP)  Publisher

keywords

• 49 Mathematical Sciences
• 4905 Statistics

Digital Object Identifier (DOI)

• 10.2307/2336606

start page

• 549

end page

• 556

volume

• 75

issue

• 3

URL

• http%3A%2F%2Fdx.doi.org%2F10.1093%2Fbiomet%2F75.3.549