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• W2113820576 abstract "I demonstrate the application of hierarchical regression modeling, a state-of-the-art technique for statistical inference, to language research. First, a stable sociolinguistic variable in Philadelphia (Labov, 2001) is reconsidered, with attention paid to the treatment of collinearities among socioeconomic predic- tors. I then demonstrate the use of hierarchical models to account for the random sampling of subjects and items in an experimental setting, using data from a study of word-learning in the face of tonal varia- tion (Quam and Swingley, forthcoming). The results from these case studies demonstrate that modeling sampling from the population has empirical consequences." @default.
• W2113820576 created "2016-06-24" @default.
• W2113820576 creator A5011757745 @default.
• W2113820576 date "2009-01-01" @default.
• W2113820576 modified "2023-09-26" @default.
• W2113820576 title "Hierarchical regression modeling for language research" @default.
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