中川和席尔泽特方法向随机斜率模型的扩展。
Extension of Nakagawa & Schielzeth's to random slopes models.
作者信息
Johnson Paul Cd
机构信息
Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow Graham Kerr Building, Glasgow, G12 8QQ, UK.
出版信息
Methods Ecol Evol. 2014 Sep;5(9):944-946. doi: 10.1111/2041-210X.12225. Epub 2014 Jul 23.
Abstract
Nakagawa & Schielzeth extended the widely used goodness-of-fit statistic to apply to generalized linear mixed models (GLMMs). However, their method is restricted to models with the simplest random effects structure, known as random intercepts models. It is not applicable to another common random effects structure, random slopes models.I show that can be extended to random slopes models using a simple formula that is straightforward to implement in statistical software. This extension substantially widens the potential application of .
摘要
中川和席尔泽特扩展了广泛使用的拟合优度统计量，使其适用于广义线性混合模型（GLMMs）。然而，他们的方法仅限于具有最简单随机效应结构的模型，即随机截距模型。它不适用于另一种常见的随机效应结构，即随机斜率模型。我表明，可以使用一个简单的公式将其扩展到随机斜率模型，该公式在统计软件中易于实现。这种扩展大大拓宽了其潜在应用范围。
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