The effect of variance function estimation on nonlinear calibration inference in immunoassay data
The effect of variance function estimation on nonlinear calibration inference in immunoassay data
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DOI：
10.2307/2533153
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发表时间：
1996-03-01
期刊：
影响因子：
1.9
通讯作者：
Giltinan, DM
中科院分区：
文献类型：
--
作者：
Belanger, BA;Davidian, M;Giltinan, DM
对于来自免疫测定的数据，浓度-响应关系通常是非线性的，并且测定内响应方差是异质的。标准曲线的估计通常基于浓度-响应的非线性异方差回归模型，其中方差建模为平均响应和其他方差参数的函数。本文讨论了具有这种非线性异方差均值-方差关系的免疫分析数据的校正推断。本文通过理论和经验研究以及两个实例的应用，对未知浓度的三种近似大样本置信区间的方差函数估计的效果进行了评估。一个主要发现是，此类校准间隔的准确性关键取决于响应方差的性质和估计方差参数的质量。
Often with data from immunoassays, the concentration-response relationship is nonlinear and intraassay 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.