O'Brien Timothy E, Silcox Jack
Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA.
Ph.D. Program in Cognitive and Neural Science, University of Utah, Salt Lake City, UT, USA.
J Appl Stat. 2021 Feb 4;48(13-15):2864-2888. doi: 10.1080/02664763.2021.1880556. eCollection 2021.
The logit binomial logistic dose response model is commonly used in applied research to model binary outcomes as a function of the dose or concentration of a substance. This model is easily tailored to assess the relative potency of two substances. Consequently, in instances where two such dose response curves are parallel so one substance can be viewed as a dilution of the other, the degree of that dilution is captured in the relative potency model parameter. It is incumbent that experimental researchers working in fields including biomedicine, environmental science, toxicology and applied sciences choose efficient experimental designs to run their studies to both fit their dose response curves and to garner important information regarding drug or substance potency. This article provides far-reaching practical design strategies for dose response model fitting and estimation of relative potency using key illustrations. These results are subsequently extended here to handle situations where the assessment of parallelism and the proper dose-scale are also of interest. Conclusions and recommended strategies are supported by both theoretical and simulation results.
对数二项逻辑剂量反应模型在应用研究中常用于将二元结果建模为物质剂量或浓度的函数。该模型易于定制以评估两种物质的相对效力。因此，在两条这样的剂量反应曲线平行，以至于一种物质可被视为另一种物质的稀释物的情况下，这种稀释程度会在相对效力模型参数中体现出来。从事生物医学、环境科学、毒理学和应用科学等领域的实验研究人员有责任选择高效的实验设计来开展研究，以拟合他们的剂量反应曲线并获取有关药物或物质效力的重要信息。本文通过关键示例提供了用于剂量反应模型拟合和相对效力估计的具有深远意义的实用设计策略。这些结果随后在此处进行扩展，以处理平行性评估和适当剂量尺度也很重要的情况。理论和模拟结果都支持了结论和推荐策略。
