gdina.wald | R Documentation |
This function tests with a Wald test for the GDINA model whether a DINA or a ACDM
condensation rule leads to a sufficient item fit compared
to the saturated GDINA rule (de la Torre & Lee, 2013). The Wald test
is accompanied by the RMSEA fit and weighted and unweighted
distance measures (wgtdist
, uwgtdist
), see Details
(compare Ma, Iaconangelo, & de la Torre, 2016).
gdina.wald(object) ## S3 method for class 'gdina.wald' summary(object, digits=3, vars=c("X2", "p", "sig", "RMSEA", "wgtdist"), ...)
object |
A fitted |
digits |
Number of digits after decimal used for rounding. |
vars |
Vector including variables which should
be displayed in |
... |
Further arguments to be passed |
Let P_j( α _l) the estimated item response function for the
GDINA model and \hat{P}_j( α _l) the item response
model for the approximated model (DINA, DINO or ACDM).
The unweighted distance uwgtdist
as a measure of misfit is defined as
uwgtdist=\frac{1}{2^K} ∑_l ( P_j( α _l) - \hat{P}_j( α _l) )^2
The weighted distance wgtdist
measures the discrepancy
with respected to the probabilities w_l=P( α_l) of estimated
skill classes
wgtdist=∑_l w_l (P_j( α _l) - \hat{P}_j( α _l) )^2
stats |
Data frame with Wald statistic for every item, corresponding p values and a RMSEA fit statistic |
de la Torre, J., & Lee, Y. S. (2013). Evaluating the Wald test for item-level comparison of saturated and reduced models in cognitive diagnosis. Journal of Educational Measurement, 50, 355-373.
Ma, W., Iaconangelo, C., & de la Torre, J. (2016). Model similarity, model selection, and attribute classification. Applied Psychological Measurement, 40(3), 200-217.
See the GDINA::modelcomp
function in the
GDINA package for similar functionality.
## Not run: ############################################################################# # EXAMPLE 1: Wald test for DINA simulated data sim.dina ############################################################################# data(sim.dina, package="CDM") data(sim.qmatrix, package="CDM") # Model 1: estimate GDINA model mod1 <- CDM::gdina( sim.dina, q.matrix=sim.qmatrix, rule="GDINA") summary(mod1) # perform Wald test res1 <- CDM::gdina.wald( mod1 ) summary(res1) # -> results show that all but one item fit according to the DINA rule # select some output summary(res1, vars=c("wgtdist", "p") ) ## End(Not run)
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