fit_m2: Estimate the M_2 fit statistic for diagnostic classification...

In wjakethompson/measr: Bayesian Psychometric Measurement Using 'Stan'

Estimate the M₂ fit statistic for diagnostic classification models

Description

For diagnostic classification models, the M₂ statistic is calculated as described by Hansen et al. (2016) and Liu et al. (2016).

Usage

## S3 method for class 'measrdcm'
fit_m2(model, ..., ci = 0.9, force = FALSE)

Arguments

model	An estimated diagnostic classification model.
...	Unused, for extensibility.
ci	The confidence interval for the RMSEA.
force	If the M2 has already been saved to the model object with add_fit(), should it be recalculated. Default is FALSE.

Value

A data frame created by dcm2::fit_m2().

Methods (by class)

• fit_m2(measrdcm): M₂ for diagnostic classification models.

References

Hansen, M., Cai, L., Monroe, S., & Li, Z. (2016). Limited-information goodness-of-fit testing of diagnostic classification item response models. British Journal of Mathematical and Statistical Psychology, 69(3), 225-252. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/bmsp.12074")}

Liu, Y., Tian, W., & Xin, T. (2016). An application of M₂ statistic to evaluate the fit of cognitive diagnostic models. Journal of Educational and Behavioral Statistics, 41(1), 3-26. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3102/1076998615621293")}

Examples

rstn_mdm_lcdm <- measr_dcm(
  data = mdm_data, missing = NA, qmatrix = mdm_qmatrix,
  resp_id = "respondent", item_id = "item", type = "lcdm",
  method = "optim", seed = 63277, backend = "rstan"
)

fit_m2(rstn_mdm_lcdm)

wjakethompson/measr documentation built on April 12, 2025, 9:46 p.m.