Mixed‐Effects Modeling with a Multinomial Dependent Variable

IF 3.5 1区文学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Language Learning Pub Date : 2024-08-26 DOI:10.1111/lang.12667

Aarnes Gudmestad, Thomas A. Metzger

引用次数: 0

Abstract

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.

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多变量混合效应模型

在这篇方法展示文章中，我们将用一个多因变量来说明混合效应模型，以此来解释语言的复杂性。我们对第二语言西班牙语的未来时间参照数据进行了建模，该数据由一个名义因变量组成，该因变量有三个水平，对 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式逻辑回归的分步程序，并讨论了模型的解释及其优势和局限性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Language Learning Multiple-

CiteScore

9.10

自引率

15.90%

发文量

期刊介绍： Language Learning is a scientific journal dedicated to the understanding of language learning broadly defined. It publishes research articles that systematically apply methods of inquiry from disciplines including psychology, linguistics, cognitive science, educational inquiry, neuroscience, ethnography, sociolinguistics, sociology, and anthropology. It is concerned with fundamental theoretical issues in language learning such as child, second, and foreign language acquisition, language education, bilingualism, literacy, language representation in mind and brain, culture, cognition, pragmatics, and intergroup relations. A subscription includes one or two annual supplements, alternating among a volume from the Language Learning Cognitive Neuroscience Series, the Currents in Language Learning Series or the Language Learning Special Issue Series.