lmer to fit a random-intercepts only model, and then uses
mcmcsamp to obtain p-values.
A dataframe formatted as described in
Whether the design is between-items (TRUE) or within-items (FALSE).
Number of Markov-Chain Monte Carlo simulations (default = 10000).
If the model does not converge, returns
NA. The MCMC procedure is
based on Baayen's
pvals.fnc in package
This function no longer works and will throw an error, as the
mcmcsamp function was removed starting with
lme4 package 1.0; see
mcmcsamp for details.
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nmc <- 10 pmx <- cbind(randParams(genParamRanges(), nmc, 1001), seed=mkSeeds(nmc, 1001)) # between-items dataset x.bi <- mkDf(nsubj=24, nitem=24, mcr.params=pmx[1,], wsbi=TRUE) # NB: small number of MCMC runs so that the example runs quickly # increase the number of runs for stable results fitnocorr.mcmc(x.bi, wsbi=TRUE, nmcmc=1000)
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