Confirmatory M2PL Analysis

Usage

C2PL_gvem(u, indic, max.iter = 5000, SE.est = FALSE)

u: an \(N \times J\) matrix or a data.frame that consists of binary responses of \(N\) individuals to \(J\) items. The missing values are coded as NA
indic: a \(J \times K\) matrix or a data.frame that describes the factor loading structure of \(J\) items to \(K\) factors. It consists of binary values where 0 refers to the item is irrelevant with this factor, 1 otherwise
max.iter: the maximum number of iterations for the EM cycle; default is 5000
SE.est: whether to estimate SE for item parameters using the updated supplemented expectation maximization (USEM); default is FALSE

a list containing the following objects:

ra: item discrimination parameters, a \(J \times K\) matrix
rb: item difficulty parameters, vector of length \(J\)
reta: variational parameters \(\eta(\xi)\), a \(N \times J\) matrix
reps: variational parameters \(\xi\), a \(N \times J\) matrix
rsigma: population variance-covariance matrix, a \(K \times K\) matrix
mu_i: mean parameter for each person, a \(K \times N\) matrix
sig_i: covariance matrix for each person, a \(K \times K \times N\) array
n: the number of iterations for the EM cycle
Q_mat: factor loading structure, a \(J \times K\) matrix
GIC: model fit index
AIC: model fit index
BIC: model fit index
SE: Standard errors of item parameters, a \(J \times (K+1)\) matrix where the last column includes SE estimates for item difficulty parameters

Jiaying Xiao <jxiao6@uw.edu>

if (FALSE) { # \dontrun{
with(C2PL_data, C2PL_gvem(data, model))} # }