is.CDMid {cdmTools} | R Documentation |
Check whether a CDM is identified
Description
Uses a post-hoc simulation approach to check whether a cognitive diagnosis model is identified (i.e., all latent classes are distinguishable; de la Torre et al., 2023).
Usage
is.CDMid(fit, N = 10000, timesJ = 20, Wald = FALSE, verbose = TRUE)
Arguments
fit |
An object of class RDINA or GDINA (Ma & de la Torre, 2020). |
N |
A numeric value that indicates the number of respondents to simulate. Default is 10000. |
timesJ |
A numeric value that indicates the number of times the test length is multiplied. Default is 20. |
Wald |
A |
verbose |
A |
Value
is.CDMid
returns an object of class is.CDMid
.
total
Overall classification accuracy (CCA) and number of posterior multiple modes (PMM). A CCA = 1 indicates that all latent classes are identified (
vector
).class
Classification accuracy (CCA) and number of posterior multiple modes (PMM) for each latent class. A CCA = 1 indicates that the latent class is identified (
data.frame
).
Author(s)
Pablo Nájera, Universidad Pontificia Comillas
References
de la Torre, J., Sorrel, M. A., & Nájera, P. (2023, July). Cognitive diagnosis modeling. Workshop at the VII International Psychometric Summer School "Applied Psychometrics in Psychology and Education". Yerevan, Armenia.
Examples
library(GDINA)
dat <- sim30GDINA$simdat
Q <- sim30GDINA$simQ
fit <- GDINA(dat, Q)
id <- is.CDMid(fit)