AVT: The Use of Linguistic Variants in Audio-Visual Translation...

In corregp: Functions and Methods for Correspondence Regression

Description

This data set was a follow-up study to the COMURE project and was conducted at the Department of Translation, Interpreting and Communication of Ghent University between 2014 and 2018.

Format

A data frame with 3302 rows and 7 variables.

• Variant The linguistic variant used in a set of alternatives (27 levels).

• Variable The linguistic variable specifying a set of alternatives (13 levels).

• Variety The dichotomization of Variant into standard and non-standard.

• Speaker The role of the speaker in the data (2 levels).

• Language The language (and source language) of the data (3 levels).

• Language2 The same as Language but with the observations of level intra.nl set to NA.

• Genre The genre or register of the data (2 levels).

Source

Prieels, L., I. Delaere, K. Plevoets and G. De Sutter (2015) A corpus-based multivariate analysis of linguistic norm-adherence in audiovisual and written translation. Across Languages and Cultures 16 (2), 209–231.

Examples

data(AVT)
# The execution of corregp may be slow, due to bootstrapping:  
avt.crg <- corregp(Variant ~ Speaker * Language * Genre, data = AVT, part = "Variable", b = 3000)
avt.crg
summary(avt.crg, parm = "b", add_ci = TRUE)
screeplot(avt.crg, add_ci = TRUE)
anova(avt.crg, nf = 2)
avt.col <- ifelse( xtabs(~ Variant + Variety, data = AVT)[, "Standard"] > 0, "blue", "red")
plot(avt.crg, x_ell = TRUE, xsub = c("Speaker", "Language", "Genre"), col_btm = avt.col, 
  col_top = "black")

corregp documentation built on May 1, 2019, 10:08 p.m.