In this Methods Showcase Article, we illustrate mixed‐effects modeling with a multinomial dependent variable as a means of explaining complexities in language. We model data on future‐time reference in second language Spanish, which consists of a nominal dependent variable that has three levels, measured over 73 participants. We offer step‐by‐step procedures for multinomial logistic regression with fixed and random effects, and we discuss the interpretation of the model and its advantages and limitations.

中文翻译：

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使用多项因变量的混合效应建模


在这篇方法展示文章中，我们说明了使用多项因变量的混合效应建模作为解释语言复杂性的一种手段。我们对第二语言西班牙语的未来时间参考数据进行了建模，其中包含一个具有三个水平的名义因变量，对超过 73 名参与者进行了测量。我们提供了具有固定效应和随机效应的多项逻辑回归的分步程序，并讨论了模型的解释及其优点和局限性。