Data sets and functions accompanying 'Analyzing Linguistic Data: A practical introduction to statistics', Cambridge University Press, 2007.
|License:||GNU public license|
The main function of this package is to make available the data sets discussed and analyzed in 'Analyzing Linguistic Data: A practical introduction to statistics using R', to appear with Cambridge University Press. The following packages should be installed, as ancillary functions in this package depend on them.
for word frequency distributions
for mixed-effects models
for Markov-Chain Monte Carlo estimation
for trellis graphics
for mixed-effects modeling
The following packages need to be installed for working through specific examples.
for regression modeling
for CART trees
for support vector machines
for many useful functions
for phylogenetic clustering
The main convenience functions in this library are, by category:
(extending code by Murtagh, 2005)
(supplementing current zipfR functionality)
for two texts, compare richness
empirical vocabulary growth data for text
conversion to vgc object of zipfR
creates frequency spectrum
conversion to spc object of zipfR
(p-values for mixed-effects models with lme4)
p-values for table of coefficients including MCMC
p-values for anova tables and/or MCMC p-value for specified factor
(for comparing mixed models with traditional techniques including F1, F2, and F1+F2)
simulate simple regression design
simulate data for Quasi-F ratios
simulating simple Latin-square design
scatterplot matrix with correlation tests
p-values and MCMC confidence intervals for mixed models
diagnostic visualization for logistic models
trellis scatterplots with smoother
scatterplot for bivariate standard normal random numbers with regression line
offers choice of four ways to visualize an interaction between two numeric predictors in an lmer model
R. H. Baayen
University of Alberta, Edmonton, Canada
Maintainer: [email protected]
R. H. Baayen (2007) Analyzing Linguistic Data: A practical introduction to statistics using R, Cambridge: Cambridge University Press.
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