normalSim {hbmem} | R Documentation |
Simulates data from a hierarchical linear normal model.
normalSim(N=1,I=30,J=300,mu=0,s2a=.2,s2b=.2,muS2=0,s2aS2=0,s2bS2=0)
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 |
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).
Michael S. Pratte
hbmem
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)