| ClassRate {GDINA} | R Documentation |
Classification Rate Evaluation
Description
This function evaluates the classification rates for two sets of attribute profiles
Usage
ClassRate(att1, att2)
Arguments
att1 |
a matrix or data frame of attribute profiles |
att2 |
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.
Author(s)
Wenchao Ma, The University of Alabama, wenchao.ma@ua.edu
References
Ma, W., & de la Torre, J. (2020). GDINA: An R Package for Cognitive Diagnosis Modeling. Journal of Statistical Software, 93(14), 1-26.
Examples
## Not run:
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
## End(Not run)