is.CDMid: Check whether a CDM is identified

In Pablo-Najera/cdmTools: Useful Tools for Cognitive Diagnosis Modeling

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 logical value that indicates whether the Wald method should be used to find the best model for each item (only applicable if fit is of class GDINA). Default is FALSE.
verbose	A logical value that indicates whether information about the process should be printed or not. Default is TRUE.

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)

Pablo-Najera/cdmTools documentation built on April 14, 2025, 10:49 a.m.