Calculate theta estimates using EB (Empirical Bayes) method
theta_EB_single and theta_EB are functions to calculate theta estimates using EB (Empirical Bayes) method.
theta_EB( nx, theta_init, theta_prop, item_parm, resp, ncat, model, prior, prior_parm ) theta_EB_single( nx, theta_init, theta_prop, item_parm, resp, ncat, model, prior, prior_parm )
nx |
the number of MCMC draws. |
theta_init |
initial estimate of theta. |
theta_prop |
SD of the proposal distribution. |
item_parm |
a matrix containing item parameters. Each row represents each item. |
resp |
a vector (or a value if for one item) containing responses on each item. |
ncat |
a vector (or a value if for one item) containing the number of response categories of each item. |
model |
a vector (or a value if for one item) indicating item models of each item, using
|
prior |
an integer indicating the type of prior distribution, using
|
prior_parm |
a vector containing parameters for the prior distribution. |
theta_EB_single is designed for one item, and theta_EB is designed for multiple items.
Currently supports unidimensional models.
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# item parameters item_parm <- matrix(c( 1, NA, NA, 1, 2, NA, 1, 2, 0.25, 0, 1, NA, 2, 0, 1, 2, 0, 2), nrow = 6, byrow = TRUE ) ncat <- c(2, 2, 2, 3, 3, 3) model <- c(1, 2, 3, 4, 5, 6) resp <- c(0, 1, 0, 1, 0, 1) nx <- 100 theta_init <- 0 theta_prop <- 1.0 set.seed(1) theta_EB_single(nx, theta_init, theta_prop, item_parm[1, ], resp[1], ncat[1], model[1], 1, c(0, 1)) theta_EB(nx, theta_init, theta_prop, item_parm, resp, ncat, model, 1, c(0, 1))
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