Analyzing linguistic data: a practical introduction to statistics using R, 1st Edition

By R. Harald Baayen. 2008

1,111 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d522336d4ac72a7620cd0c9488d37920443ade02

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Citations in the corpus

Influence of initial plant density on sawn timber properties for Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) (2014, methodology): “All data were analyzed using R (R Development Core Team 2012) and the R package lme4 (Bates and Maechler 2009) and languageR (Baayen 2008).”
Effects of primary and secondary morphological family size in monolingual and bilingual word processing (2014, methodology): “Furthermore, to be able to remove any auto-correlation from the error, we included PreviousRT (the logarithmically transformed response latency at the previous trial) and Trial (the rank of the item in the experimental list) as predictors (cf. Baayen, 2008 and Baayen & Milin, 2010).”
To transform or not to transform: using generalized linear mixed models to analyse reaction time data (2015, unknown): “For over 100 years, cognitive psychologists have used RT to investigate unobservable mental processes (Donders, 1868/1969; Luce, 1986). These investigations are based on two fundamental assumptions: (i) mental processes take time to complete, and that (ii) each measured RT reflects a composite of se”
Voluntary language switching: When and why do bilinguals switch between their languages? (2018, methodology): “16 predictors and compared the simpler model to the full model using likelihood-ratio chisquare tests (Baayen, 2008).”
Children's developing understanding of legitimate reasons for allocating resources unequally (2016, methodology): “For binary outcome variables, we used Generalized Linear Mixed Models (GLMMs) with binomial error structure (Baayen, 2008; Bates, Maechler, Bolker, & Walker, 2013).”
Making choices in Russian: pros and cons of statistical methods for rival forms (2013, methodology): “This explains the term ʻmixed modelʼ: 1151 it is a model that ʻmixesʼ fixed-effect and random-effect factors in one and the 1152 same analysis (cf. Baayen 2008, Chapter 7).”
Models, forests, and trees of York English: Was/were variation as a case study for statistical practice (2012, methodology): “…to come to grips with an essential source of variation, but they also run the risk of reporting a result as significant that upon closer inspection turns out not to be not significant, in other words, an anticonservative interpretation of results (see, e.g., Baayen, 2008; Baayen et al., 2008).”
Which-hunting and the Standard English relative clause (2015, background): “The model’s condition number κ is 17.6, which is another way of saying that the model exhibits moderate, though not harmful (Baayen 2008:182), collinearity.”