This function evaluates the classification rates for two sets of attribute profiles

ClassRate(att1, att2)

## Arguments

att1 a matrix or data frame of attribute profiles a matrix or data frame of attribute profiles

## Value

a list with the following components:

PCA

the proportion of correctly classified attributes (i.e., attribute level classification rate)

PCV

a vector giving the proportions of correctly classified attribute vectors (i.e., vector level classification rate). The fist element is the proportion of at least one attribute in the vector are correctly identified; the second element is the proportion of at least two attributes in the vector are correctly identified; and so forth. The last element is the proportion of all elements in the vector are correctly identified.

## Examples

if (FALSE) {
N <- 2000
# model does not matter if item parameter is probability of success
Q <- sim30GDINA$simQ J <- nrow(Q) gs <- matrix(0.1,J,2) set.seed(12345) sim <- simGDINA(N,Q,gs.parm = gs) GDINA.est <- GDINA(sim$dat,Q)

CR <- ClassRate(sim\$attribute,personparm(GDINA.est))
CR
}