createParamMx: Create Population Parameter Matrix for One-Factor Design
In dalejbarr/simgen: Monte Carlo Simulations of Simultaneous Generalization

Description Usage Arguments Details Value See Also Examples

Create a matrix of population parameters for Monte Carlo simulation with one-factor design.

1 2	createParamMx(nexp = 1e+05, simparam.env = getParamRanges(), firstseed = 666, h0 = TRUE, outfile = NULL)

`nexp`	Number of experiments to run (default 100000).
`simparam.env`	An `environment` object containing the parameter ranges; see `getParamRanges` (default) for the appropriate format.
`firstseed`	First seed to start off generation of the matrix. Included for replicability of results. A parameter matrix of a given size with a given seed will always be identical.
`h0`	Status of the null hypothesis: TRUE or FALSE.
`outfile`	Name of a file where the matrix will be stored; if NULL (default), no data will be stored.

Each row of the matrix returned from this function represents the population parameters for a given experiment. As of version 1.6 of simgen, This function has been superceded by genParamRanges and randParams, but is preserved for backwards compatibility.

A matrix, with the following columns:

`int`	(grand mean) intercept
`eff`	treatment effect
`err`	error variance
`miss`	proportion of response values missing
`t00`	by-subject intercept variance
`t11`	by-subject slope variance
`rsub`	by-subject intercept/slope correlation
`w00`	by-item intercept variance
`w11`	by-item slope variance
`ritm`	by-item intercept/slope correlation
`seed`	random number seed for creating the dataframe (see

mkDf)

getParamRanges, mkDf

# using defaults
createParamMx(10)

# now let's change one of the ranges
p.env <- getParamRanges()
get("t11.range", env=p.env)
assign("t11.range", c(5,10), env=p.env)
createParamMx(10, simparam.env=p.env)