simulateLatinsquare.fnc: Simulate simple Latin Square data and compare models

In languageR: Analyzing Linguistic Data: A Practical Introduction to Statistics

Description

This function creates a user-specified number of simulated datasets with a Latin Square design, and compares mixed-effects models with the by-subject anova.

Usage

simulateLatinsquare.fnc(dat, with = TRUE, trial = 0, nruns = 100, 
   nsub = NA, nitem = NA, ...)

Arguments

dat	A data frame with the structure of the data set latinsquare.
with	Logical, if TRUE, effect of SOA built into the data.
trial	A number which, if nonzero, gives the magnitude of a learning or a fatigue effect.
nruns	A number indicating the required number of simulation runs.
nsub	A number for the number of subjects.
nitem	A number for 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.

Author(s)

R. H. Baayen

Examples

## Not run: 
  data(latinsquare)
	\dontrun{
	library(lme4)
  simulateLatinsquare.fnc(latinsquare, nruns=100)
	}

## End(Not run)

languageR documentation built on May 2, 2019, 10:02 a.m.