| latinsquare {languageR} | R Documentation |
Simulated lexical decision latencies with SOA as treatment, using a Latin Square design with subjects and items, as available in Raaijmakers et al. (1999).
data(latinsquare)
A data frame with 144 observations on the following 6 variables.
GroupG1, G2 and
G3, for groups of subjectsSubjectS1, ... S12.WordW1 ... W12.RTSOAlong, medium,
and short.ListL1, L2, and L3
for lists of words.Raaijmakers, J.G.W., Schrijnemakers, J.M.C. & Gremmen, F. (1999) How to deal with "The language as fixed effect fallacy": common misconceptions and alternative solutions, Journal of Memory and Language, 41, 416-426.
data(latinsquare) ## Not run: library(lme4) latinsquare.with = simulate.latinsquare.fnc(latinsquare, nruns = 1000, with = TRUE) latinsquare.without = simulate.latinsquare.fnc(latinsquare, nruns = 1000, with = FALSE) latinsquare.with$alpha05 latinsquare.without$alpha05 ## End(Not run)