simulateQuasif.fnc: Simulate data for quasi-F analysis and compare models

Description

This function creates a user-specified number of simulated datasets, and compares mixed-effects models with quasi-F and F1 and F2 analyses. It should be run with the version of R and the version of languageR used by Baayen, Davidson & Bates (2008, JML), as mcmcsamp no longer supports models with random correlation parameters.

Usage

simulateQuasif.fnc(dat, with = TRUE, nruns = 100, nsub = NA, nitem = NA, ...)

Arguments

dat

Data frame with a data set with as variables Subject, Item and SOA, as in the quasif data set.

with

Logical, if TRUE, an effect of SOA is built into the simulation.

nruns

Integer for the number of simulation runs.

nsub

Integer denoting the number of subjects.

nitem

Integer denoting the number of items.

...

other parameters to be passed through to plotting functions.

Value

A list with components

alpha05

Description of 'comp1'

alpha01

proportion of runs in which predictors are significant at the 05 significance level.

res

Data frame with simulation results.

with

Logical, TRUE if SOA effect is built into the simulations.

Details

Model parameters are estimated from the input data set.

For each completed simulation run, a dot is added to the R console.

Examples

Run this code

# NOT RUN {
data(quasif)
library(lme4)

quasif.sim = simulateQuasif.fnc(quasif, nruns = 1000, with = TRUE) 
quasif.sim$alpha05
# }