hbmem (version 0.2)

uvsdLogLike: Function uvsdLogLike

Description

Computes log likelihood for UVSD model

Usage

uvsdLogLike(R,NN,NS,I,J,K,dat,cond,Scond,subj,item,lag,blockN,blockS,blockS2,crit)

Arguments

R

Total number of trials.

NN

Number of new-item conditions.

NS

Number of studied-item conditions.

I

Number of subjects.

J

Number of items.

K

Number of response options.

dat

Vector of responses, ranging from 0:(K-1).

cond

Vector of condition index.

Scond

Vector of new/studied condition index; 0=new, 1=studied.

subj

Vector of subject index, starting at 0 with no missing subject numbers.

item

Vector of item index, starting at 0 with no missing item numbers.

lag

Vector of lag index.

blockN

Block of parameters for new-item means.

blockS

Block of parameters for studied-item means.

blockS2

Block of parameters for Sigma2 values. If there is only one Sigma2 for all participants and items, then the first element of blockS2 should contain this value, and the other elements fo blockS2 should be zero.

crit

VECTOR of criteria including -Inf and Inf for top and bottom critieria, respectively. Vector contains the (K+1) criteria for the first subjects, followed by those for the second subject, etc.

Value

• The function returns the log likelihood.

References

See Pratte, Rouder, & Morey (2009)

See Also

hbmem