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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)
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).
Number of conditions.
Number of participants.
Number of items.
Grand mean
Variance of subject effect on the mean
Variance of item effect on the mean
Overall variance of data on log scale
Variance of subject effect on variance
Variance of item effect on variance
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)
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