Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models:: The npde add-on package for R
Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models:: The npde add-on package for R
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DOI：
10.1016/j.cmpb.2007.12.002
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发表时间：
2008-05-01
影响因子：
6.1
通讯作者：
Mentre, France
中科院分区：
文献类型：
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作者：
Comets, Emmanuelle;Brendel, Karl;Mentre, France
药代动力学/药效数据通常使用非线性混合效应模型进行分析，模型评估应该是分析的重要组成部分。最近，标准化预测分布误差（npde）被提出作为模型评估工具。在本文中，我们描述了开源统计包 R 的附加包，旨在计算 npde。 npde 考虑每个单独观察的完整预测分布并处理受试者内的多个观察。在所审查的模型描述验证数据集的原假设下，npde 应遵循标准正态分布。需要事先进行模拟，例如使用用于模型估计的软件。我们用两个模拟数据集（一个在真实模型下，另一个具有不同的参数值）来说明该包的使用，以展示如何使用 npde 来评估模型。使用 NONMEM 5.1 版进行模型估计和数据模拟。 (c) 2007 Elsevier Ireland Ltd. 保留所有权利
Pharmacokinetic/pharmacodynamic data are often analysed using nonlinear mixed-effect models, and model evaluation should be an important part of the analysis. Recently, normalised prediction distribution errors (npde) have been proposed as a model evaluation tool. In this paper, we describe an add-on package for the open source statistical package R, designed to compute npde. npde take into account the full predictive distribution of each individual observation and handle multiple observations within subjects. Under the null hypothesis that the model under scrutiny describes the validation dataset, npde should follow the standard normal distribution. Simulations need to be performed before hand, using for example the software used for model estimation. we illustrate the use of the package with two simulated datasets, one under the true model and one with different parameter values, to show how npde can be used to evaluate models. Model estimation and data simulation were performed using NONMEM version 5.1. (c) 2007 Elsevier Ireland Ltd. All rights reserved