Université de Paris, INSERM, IAME, F-75006, Paris, France.
INSERM, CIC1414, Université Rennes-1, 35000, Rennes, France.
AAPS J. 2021 May 19;23(4):75. doi: 10.1208/s12248-021-00597-7.
This article revisits 20 years of our work in developing evaluation tools adapted to non-linear mixed effect models. These hierarchical models involve a large number of assumptions concerning the structural evolution of the outcomes, the link between different outcomes, the variabilities in the parameters and model evaluation aims at assessing these various components, both to help guide the model building and to communicate on model adequacy for a given purpose. During our career, we have developed and extended simulation-based evaluation tools called normalised prediction discrepancies (npd) and normalised prediction distribution errors (npde), providing informative diagnostics through graphs and tests.
本文回顾了我们 20 年来开发适用于非线性混合效应模型的评估工具的工作。这些分层模型涉及到关于结果结构演变、不同结果之间的联系、参数变异性的大量假设，模型评估旨在评估这些不同的组件，以帮助指导模型构建并就给定目的的模型充分性进行交流。在我们的职业生涯中，我们开发并扩展了基于模拟的评估工具，称为归一化预测差异（npd）和归一化预测分布误差（npde），通过图形和测试提供有信息的诊断。
