Examination for the Certificate of Proficiency in English (ECPE) data (the grammar section) has been used in Henson and Templin (2007), Templin and Hoffman (2013), Feng, Habing, and Huebner (2014), and Templin and Bradshaw (2014), among others.

ecpe

Format

A list of responses and Q-matrix with components:

dat

Responses of 2922 examinees to 28 items.

Q

The \(28 \times 3\) Q-matrix.

Details

The data consists of responses of 2922 examinees to 28 items involving 3 attributes. Attribute 1 is morphosyntactic rules, Attribute 2 is cohesive rules and Attribute 3 is lexical rules.

References

Feng, Y., Habing, B. T., & Huebner, A. (2014). Parameter estimation of the reduced RUM using the EM algorithm. Applied Psychological Measurement, 38, 137-150.

Henson, R. A., & Templin, J. (2007, April). Large-scale language assessment using cognitive diagnosis models. Paper presented at the annual meeting of the National Council for Measurement in Education in Chicago, Illinois.

Templin, J., & Bradshaw, L. (2014). Hierarchical diagnostic classification models: A family of models for estimating and testing attribute hierarchies. Psychometrika, 79, 317-339.

Templin, J., & Hoffman, L. (2013). Obtaining diagnostic classification model estimates using Mplus. Educational Measurement: Issues and Practice, 32, 37-50.

Examples

if (FALSE) { mod1 <- GDINA(ecpe$dat,ecpe$Q) mod1 summary(mod1) mod2 <- GDINA(ecpe$dat,ecpe$Q,model="RRUM") mod2 anova(mod1,mod2) # You may compare the following results with Feng, Habing, and Huebner (2014) coef(mod2,"rrum") # G-DINA with hierarchical structure # see Templin & Bradshaw, 2014 ast <- att.structure(list(c(3,2),c(2,1)),K=3) est.gdina2 <- GDINA(ecpe$dat,ecpe$Q,model = "GDINA", control = list(conv.crit = 1e-6), att.str = list(c(3,2),c(2,1))) # see Table 7 in Templin & Bradshaw, 2014 summary(est.gdina2) }