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            Website of R. Harald Baayen

          Professor of Quantitative Linguistics

 

 

Software

 

The R package itsadug (Jacolien van Rij, Martijn Wieling, R. Harald Baayen, & Hedderik van Rijn (2015). itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs. R package version 0.8.) provides a range of functions facilitating the visualization and evaluation of generalized additive mixed models fit with the mgcv package of Wood (2006, 2011). [see how to install].


The languageR package, see Baayen, R. H. (2008). Analyzing Linguistic Data. A Practical Introduction to Statistics Using R, Cambridge University Press, provides datasets and some R-functions that facilitate statistical analysis. The languageR package has some added functionality that is not documented in the above mentioned book. The following code illustrates the basic functionality of plotLMER.fnc, a function for graphing the partial effects of fixed-effect factors and covariates of mixed-effects models created with lmer() from the lme4 package. It is possible to customize individual panels, to plot splines, and to visualize two-way interactions. For details, please consult the documentation (?plotLMER.fnc).

r
plot

The function acf.fnc is useful for exploring autocorrelational structure in successive trails in tasks such as lexical decision and naming.

> library(languageR)
> acf.fnc(beginningReadres, x="LogRT")


plot

Each panel represents a subject (primary school children), and displays the autocorrelation function for that subject. For some readers, response latencies at lag 20 are still correlated.



R code for complexity-based ordering as discussed in Plag and Baayen, Language, 2009 is available here. The data set for this code is available here. If code and data file are available in the current working directory, the following lines of R code produces the graphs shown below.

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adj

Figure 1: the unordered adjacency matrix

adj

Figure 2: the same adjacency matrix for complexity-based ordering


di

Figure 3: the corresponding directed graph for complexity-based ordering