Ferguson Jake M, Miura Tanya A, Miller Craig R
Center for Modeling Complex Interactions, University of Idaho, Moscow, Idaho.
Current address: Department of Biology, University of Hawai'i at Mānoa, Honolulu, Hawai'i.
Biometrics. 2019 Sep;75(3):1009-1016. doi: 10.1111/biom.13032. Epub 2019 Apr 3.
Dilution assays to determine solute concentration have found wide use in biomedical research. Many dilution assays return imprecise concentration estimates because they are only done to orders of magnitude. Previous statistical work has focused on how to design efficient experiments that can return more precise estimates, however this work has not considered the practical difficulties of implementing these designs in the laboratory. We developed a two-stage experiment with a first stage that obtains an order of magnitude estimate and a second stage that concentrates effort on the most informative dilution to increase estimator precision. We show using simulations and an empirical example that the best two-stage experimental designs yield estimates that are remarkably more accurate than standard methods with equivalent effort. This work demonstrates how to utilize previous advances in experimental design in a manner consistent with current laboratory practice. We expect that multi-stage designs will prove to be useful for obtaining precise estimates with minimal experimental effort.
用于确定溶质浓度的稀释试验在生物医学研究中得到了广泛应用。许多稀释试验返回的浓度估计值不准确，因为它们只做到了数量级。以往的统计工作主要集中在如何设计高效的实验以返回更精确的估计值，然而这项工作并未考虑在实验室中实施这些设计的实际困难。我们开发了一种两阶段实验，第一阶段获得数量级估计值，第二阶段将精力集中在信息量最大的稀释上以提高估计精度。我们通过模拟和一个实证例子表明，最佳的两阶段实验设计所产生的估计值比同等工作量的标准方法要准确得多。这项工作展示了如何以与当前实验室实践相一致的方式利用实验设计的先前进展。我们预计，多阶段设计将被证明对于以最少的实验工作量获得精确估计值是有用的。
