CM: Calculate Misclassification Matrices

In GDINA: The Generalized DINA Model Framework

Calculate Misclassification Matrices

Description

This function computes profile-level and attribute-level misclassification matrices from a fitted GDINA model. This function is only applicable to models with binary attributes.

Usage

CM(object, classification = "MAP", matrixtype = "profile")

Arguments

object	An estimated GDINA object returned from GDINA.
classification	A character string specifying the classification rule. Supported values are "MAP", "MLE", and "EAP". Alternatively, a matrix of user-supplied classifications can be provided, with one row per respondent and one column per attribute.
matrixtype	A character string specifying which matrix to return. Supported values are "profile", "attribute", and "both".

Details

The profile-level matrix is computed from posterior latent class probabilities. The attribute-level matrices are computed from marginal attribute mastery probabilities and the chosen classifications.

Value

Depending on matrixtype, the function returns one of the following:

"profile"

A class-by-class matrix of estimated P(\hat{\alpha} = c' \mid \alpha = c).

"attribute"

A list of 2 \times 2 matrices, one for each attribute, with estimated P(\hat{\alpha}_k = a' \mid \alpha_k = a).

"both"

A list with elements profile_classification and att_classification.

For both pattern-level and attribute-level matrices, rows correspond to true classes and columns correspond to classified classes.

Author(s)

Wenchao Ma, The University of Minnesota, [e-mail]

Examples

## Not run: 
dat <- realdata_ECPE$dat
Q <- realdata_ECPE$Q
fit <- GDINA(dat = dat, Q = Q, model = "GDINA")
CM(fit)
CM(fit, matrixtype = "both")

## End(Not run)

GDINA documentation built on Oct. 6, 2026, 1:07 a.m.