Conditional weighted residuals (CWRES): A model diagnostic for the FOCE method
Conditional weighted residuals (CWRES): A model diagnostic for the FOCE method
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DOI：
10.1007/s11095-007-9361-x
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发表时间：
2007-12-01
影响因子：
3.7
通讯作者：
Karlsson, Mats O.
中科院分区：
文献类型：
--
作者：
Hooker, Andrew C.;Staatz, Christine E.;Karlsson, Mats O.
目的。总体模型分析已从使用一阶 (FO) 转变为使用条件估计 (FOCE) 逼近真实模型的一阶。然而，加权残差 (WRES)（一种用于测试模型错误指定的常用诊断工具）是使用 FO 近似计算的。将 WRES 与 FOCE 方法结合使用可能会导致模型开发/评估出现误导。我们提出了一种新的诊断工具，即条件加权残差 (CWRES)，它是根据 FOCE 近似计算的。材料和方法。 CWRES 的计算方式为个体数据与该数据的模型预测之间的 FOCE 近似差异除以给定模型的数据协方差的根。结果。使用真实数据和模拟数据，CWRES 分布在正确模型下的表现符合理论预期。相反，在某些情况下，WRES 的分布大大偏离预期，错误地表明模型指定错误。 CWRES/WRES 比较还可以表明 FOCE 估计方法是否会改进 FO 模型拟合数据的结果。结论。使用 CWRES 可以改进模型开发和评估，并更准确地了解使用 FO 或 FOCE 方法时模型是否以及何时指定错误。
Purpose. Population model analyses have shifted from using the first order (FO) to the first-order with conditional estimation (FOCE) approximation to the true model. However, the weighted residuals (WRES), a common diagnostic tool used to test for model misspecification, are calculated using the FO approximation. Utilizing WRES with the FOCE method may lead to misguided model development/evaluation. We present a new diagnostic tool, the conditional weighted residuals (CWRES), which are calculated based on the FOCE approximation.Materials and Methods. CWRES are calculated as the FOCE approximated difference between an individual's data and the model prediction of that data divided by the root of the covariance of the data given the model.Results. Using real and simulated data the CWRES distributions behave as theoretically expected under the correct model. In contrast, in certain circumstances, the WRES have distributions that greatly deviate from the expected, falsely indicating model misspecification. CWRES/WRES comparisons can also indicate if the FOCE estimation method will improve the results of an FO model fit to data.Conclusions. Utilization of CWRES could improve model development and evaluation and give a more accurate picture of if and when a model is misspecified when using the FO or FOCE methods.