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计算归一化预测分布误差以评估非线性混合效应模型:用于R的npde附加包。

Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: the npde add-on package for R.

作者信息

Comets Emmanuelle, Brendel Karl, Mentré France

机构信息

INSERM, U738, Paris, France.

出版信息

Comput Methods Programs Biomed. 2008 May;90(2):154-66. doi: 10.1016/j.cmpb.2007.12.002. Epub 2008 Jan 22.

Abstract

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.

摘要

药代动力学/药效学数据通常使用非线性混合效应模型进行分析,模型评估应是分析的重要组成部分。最近,已提出将标准化预测分布误差(npde)作为一种模型评估工具。在本文中,我们描述了一个用于开源统计软件包R的附加包,旨在计算npde。npde考虑了每个个体观测值的完整预测分布,并处理个体内的多个观测值。在被审查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说明了该软件包的使用,一个基于真实模型,另一个具有不同的参数值,以展示如何使用npde评估模型。模型估计和数据模拟使用NONMEM版本5.1进行。

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