fit_m2.measrdcm {measr}R Documentation

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, ...)

Arguments

model

An estimated diagnostic classification model.

ci

The confidence interval for the RMSEA.

...

Unused, for extensibility.

Value

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

Methods (by class)

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. 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. 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)


[Package measr version 0.3.1 Index]