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)
``` |

dalejbarr/simgen documentation built on Jan. 28, 2019, 7:43 p.m.

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