hbmem (version 0.2)

normalSim: Function normalSim

Description

Simulates data from a hierarchical linear normal model.

Usage

normalSim(N=1,I=30,J=300,mu=0,s2a=.2,s2b=.2,muS2=0,s2aS2=0,s2bS2=0)

Arguments

N

Number of conditions.

I

Number of participants.

J

Number of items.

mu

Grand mean

s2a

Variance of subject effect on the mean

s2b

Variance of item effect on the mean

muS2

Overall variance of data on log scale

s2aS2

Variance of subject effect on variance

s2bS2

Variance of item effect on variance

Value

• The function returns a data frame with subject (subj), item, lag, and response (resp) columns. Lag is a vector of zeros (i.e., no lag effect).

See Also

hbmem

Examples

library(hbmem)
I=20
J=50
R=I*J
dat=normalSim(I=I,J=J,mu=10,s2a=1,s2b=1,muS2=log(1),s2aS2=0,s2bS2=0)
summary(dat)