论文标题
混合效应模型测定系数
Coefficients of Determination for Mixed-Effects Models
论文作者
论文摘要
线性模型的确定系数已很好地定义，并且长期以来，对于混合效应模型而言，它的扩展已被通缉。我们重新审视其扩展，以定义由整个模型，仅固定效应和随机效应所解释的变异比例的度量。我们建议计算以个人随机和/或固定效果为条件的无法解释的变化，以使可用预测因子带来单个异质性。虽然天然定义了用于线性混合模型的定义，但可以使用沿其方差函数测量的距离为广义线性混合模型定义这些度量，从而考虑了其异方差。
The coefficient of determination is well defined for linear models and its extension is long wanted for mixed-effects models. We revisit its extension to define measures for proportions of variation explained by the whole model, fixed effects only, and random effects only. We propose to calculate unexplained variations conditional on individual random and/or fixed effects so as to keep individual heterogeneity brought by available predictors. While naturally defined for linear mixed models, these measures can be defined for a generalized linear mixed model using a distance measured along its variance function, accounting for its heteroscedasticity.
