Enzyme-linked immunosorbent assays (ELISAs) are often used to quantify the concentration of biological substances. In a typical analysis only a point estimate of the concentration will be presented as interval estimation continues to present challenges for non-linear dose-response models. In this setting, interval estimates calculated using a Wald approach can suffer from poor coverage and have limits that fall outside parameter boundaries. Here we compare profile likelihood interval estimation procedures to Wald type intervals for the interval estimation of a concentration in the ELISA setting. Through a comprehensive simulation study, it is shown that profile likelihood methods result in interval estimates with superior coverage and that are more robust to differences in assay design when compared to Wald based approaches.

酶联免疫吸附测定 (ELISA) 通常用于量化生物物质的浓度。在典型的分析中，只会呈现浓度的点估计，因为区间估计继续对非线性剂量反应模型提出挑战。在这种情况下，使用 Wald 方法计算的区间估计可能存在覆盖率差的问题，并且具有超出参数边界的限制。在这里，我们将轮廓似然区间估计程序与 Wald 类型区间进行比较，以在 ELISA 设置中对浓度进行区间估计。通过全面的模拟研究，结果表明，与基于 Wald 的方法相比，轮廓似然方法产生的区间估计具有更高的覆盖范围，并且对分析设计的差异更加稳健。