Description Usage Arguments Details Value Author(s) References See Also Examples
This function fits Rasch family models using pseudolikelihood esitmation. It is capable of dealing with polytomous items, and multidimensional latent variables.
1 |
data |
is a data frame or matrix with rows indicating individuals, columns indicating items, and the entry values indicating the choices. |
item.mtx |
is the adjacency matrix between items and latent traits |
trait.mtx |
is the adjacency matrix for latent traits |
The model is
\preformatted{ exp( w[i,h]' theta[v] + beta[i,h] ) P(X[v,i] = h) = --------------------------------------------- sum_l exp( w[i,l]' theta[v] + beta[i,l] ) }
where
X[v,i] is the response of vth individual to ith item; w[i,h] is a vector of known category weights or scores for response h of ith item; theta[v] is a vector of latent traits for vth individual; beta[i,h] is the item difficulty parameter for ith item; associated with response h.
The function only returns the item parameter beta.
Essentially, it is a wrapper function: the equvialent llla model is fitted.
coefficients |
estimated item parameter beta |
se |
standard error of beta |
covb |
covariance matrix of the estimated parameter beta |
Zhushan "Mandy" Li & Feng Hong
Anderson, C.J., Li, Z., & Vermunt, J.K. (2007). Estimation of models in the Rasch family for polytomous items and multiple latent variables. Journal of Statistical Software, 20.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | NCAT <- 2;
NITEM <- 4;
NEXAMINEE <- 50;
BETA <- c(-1, 0, 0.5, 1)
set.seed(1);
rasch.sim <- simRasch(ncat=NCAT, nitem=NITEM, nexaminee=NEXAMINEE, beta=BETA)
sim.data <- rasch.sim$data
colnames(sim.data) <- paste("I", 1:NITEM, sep='')
## The model item adjacency matrix and the latent trait adjacency matrix
item.mtx <- rep(1, NITEM);
trait.mtx <- 1;
plfit.rasch <- RaschPLE(sim.data, item.mtx, trait.mtx)
plfit.rasch
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