languageR (version 1.0)

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

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.

Examples

data(latinsquare)
	\dontrun{
	library(lme4)
  simulateLatinsquare.fnc(latinsquare, nruns=100)
	}