Evaluation of Likelihood
The function eval_likelihood evaluates the likelihood given item
responses and item response probabilities.
The function prep_data_long_format stores the matrix of
item responses in a long format omitted all missing responses.
eval_likelihood(data, irfprob, prior=NULL, normalization=FALSE, N=NULL) prep_data_long_format(data)
data |
Dataset containing item responses in wide format or long format
(generated by |
irfprob |
Array containing item responses probabilities, format
see |
prior |
Optional prior (matrix or vector) |
normalization |
Logical indicating whether posterior should be normalized |
N |
Number of persons (optional) |
Numeric matrix
## Not run:
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# EXAMPLE 1: Likelihood data.ecpe
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data(data.ecpe, package="CDM")
dat <- data.ecpe$dat[,-1]
Q <- data.ecpe$q.matrix
#*** store data matrix in long format
data_long <- CDM::prep_data_long_format(data)
str(data_long)
#** estimate GDINA model
mod <- CDM::gdina(dat, q.matrix=Q)
summary(mod)
#** extract data, item response functions and prior
data <- CDM::IRT.data(mod)
irfprob <- CDM::IRT.irfprob(mod)
prob_theta <- attr( irfprob, "prob.theta")
#** compute likelihood
lmod <- CDM::eval_likelihood(data=data, irfprob=irfprob)
max( abs( lmod - CDM::IRT.likelihood(mod) ))
#** compute posterior
pmod <- CDM::eval_likelihood(data=data, irfprob=irfprob, prior=prob.theta,
normalization=TRUE)
max( abs( pmod - CDM::IRT.posterior(mod) ))
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.