onze_intercepts: Speaker random intercepts from GAMMs for 100 ONZE speakers

Description

A dataset containing the speaker intercepts extracted from GAMM models fit in Brand et al. (2021).

Usage

onze_intercepts

Arguments

Format

A data frame with 100 rows and 21 variables:

speaker: Anonymised speaker code (character).
F1_DRESS: Speaker intercept from GAMM model of DRESS F1.
F2_DRESS: Speaker intercept from GAMM model of DRESS F2.
F1_FLEECE: Speaker intercept from GAMM model of FLEECE F1.
F2_FLEECE: Speaker intercept from GAMM model of FLEECE F2.
F1_GOOSE: Speaker intercept from GAMM model of GOOSE F1.
F2_GOOSE: Speaker intercept from GAMM model of GOOSE F2.
F1_KIT: Speaker intercept from GAMM model of KIT F1.
F2_KIT: Speaker intercept from GAMM model of KIT F2.
F1_LOT: Speaker intercept from GAMM model of LOT F1.
F2_LOT: Speaker intercept from GAMM model of LOT F2.
F1_NURSE: Speaker intercept from GAMM model of NURSE F1.
F2_NURSE: Speaker intercept from GAMM model of NURSE F2.
F1_START: Speaker intercept from GAMM model of START F1.
F2_START: Speaker intercept from GAMM model of START F2.
F1_STRUT: Speaker intercept from GAMM model of STRUT F1.
F2_STRUT: Speaker intercept from GAMM model of STRUT F2.
F1_THOUGHT: Speaker intercept from GAMM model of THOUGHT F1.
F2_THOUGHT: Speaker intercept from GAMM model of THOUGHT F2.
F1_TRAP: Speaker intercept from GAMM model of TRAP F1.
F2_TRAP: Speaker intercept from GAMM model of TRAP F2.

References

Brand, James, Jen Hay, Lynn Clark, Kevin Watson & Márton Sóskuthy (2021): Systematic co-variation of monophthongs across speakers of New Zealand English. Journal of Phonetics. Elsevier. 88. 101096. doi:10.1016/j.wocn.2021.101096