normalSim {hbmem}R Documentation

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).

Author(s)

Michael S. Pratte

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)

[Package hbmem version 0.2 Index]