The effect of variance function estimation on nonlinear calibration inference in immunoassay data.
Journal Article (Journal Article)
Often with data from immunoassays, the concentration-response relationship is nonlinear and intra-assay response variance is heterogeneous. Estimation of the standard curve is usually based on a nonlinear heteroscedastic regression model for concentration-response, where variance is modeled as a function of mean response and additional variance parameters. This paper discusses calibration inference for immunoassay data which exhibit this nonlinear heteroscedastic mean-variance relationship. An assessment of the effect of variance function estimation in three types of approximate large-sample confidence intervals for unknown concentrations is given by theoretical and empirical investigation and application to two examples. A major finding is that the accuracy of such calibration intervals depends critically on the nature of response variance and the quality with which variance parameters are estimated.
- Belanger, BA; Davidian, M; Giltinan, DM
- March 1996
Volume / Issue
- 52 / 1
Start / End Page
- 158 - 175
International Standard Serial Number (ISSN)
- United States