Description Usage Arguments Details Note See Also Examples
Uses lmer
to fit a random-intercepts only model, and then uses
mcmcsamp
to obtain p-values.
1 | fitnocorr.mcmc(mcr.data, wsbi = FALSE, nmcmc = 10000)
|
mcr.data |
A dataframe formatted as described in |
wsbi |
Whether the design is between-items (TRUE) or within-items (FALSE). |
nmcmc |
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 languageR
.
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.
slopes.
1 2 3 4 5 6 7 8 9 | 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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