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, 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 |
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. 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)