data.timss07.G4.lee {CDM}R Documentation

TIMSS 2007 Mathematics 4th Grade (Lee et al., 2011)

Description

TIMSS 2007 (Grade 4) dataset with 25 mathematics (dichotomized) items used in Lee, Park and Taylan (2011), Park and Lee (2014) and Park, Xing and Lee (2018). The dataset includes a sample of 698 Austrian students.

Usage

data(data.timss07.G4.lee)
data(data.timss07.G4.py)
data(data.timss07.G4.Qdomains)

Format

Source

TIMSS 2007 study, 4th Grade, Austrian sample on booklets 4 and 5

References

Lee, Y. S., Park, Y. S., & Taylan, D. (2011). A cognitive diagnostic modeling of attribute mastery in Massachusetts, Minnesota, and the US national sample using the TIMSS 2007. International Journal of Testing, 11, 144-177.

Park, Y. S., & Lee, Y. S. (2014). An extension of the DINA model using covariates: Examining factors affecting response probability and latent classification. Applied Psychological Measurement, 38(5), 376-390.

Park, Y. S., Xing, K., & Lee, Y. S. (2018). Explanatory cognitive diagnostic models: Incorporating latent and observed predictors. Applied Psychological Measurement, 42(5), 376-392.

Yamaguchi, K., & Okada, K. (2018). Comparison among cognitive diagnostic models for the TIMSS 2007 fourth grade mathematics assessment. PloS ONE, 13(2), e0188691.

See Also

A comparison of several countries based on the 25 items is conducted in Yamaguchi and Okada (2018).

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: DINA model Lee et al. (2011) - 15 skills
#############################################################################

data(data.timss07.G4.lee, package="CDM")
dat <- data.timss07.G4.lee$data
q.matrix <- data.timss07.G4.lee$q.matrix
# extract items
items <- grep( "M0", colnames(dat), value=TRUE )

#*** Model 1: estimate DINA model
mod1 <- CDM::din( dat[,items], q.matrix )
summary(mod1)

#############################################################################
# EXAMPLE 2: DINA models Park and Lee (2014) - 7 skills and 3 skills
#############################################################################

data(data.timss07.G4.lee, package="CDM")
data(data.timss07.G4.py, package="CDM")
data(data.timss07.G4.Qdomains, package="CDM")

dat <- data.timss07.G4.lee$data
q.matrix <- data.timss07.G4.py$q.matrix
items <- rownames(q.matrix)

#*** Model 1: estimate DINA model
mod1 <- CDM::din( dat[,items], q.matrix )
summary(mod1)

#*** Model 2: estimate DINA model with Q-matrix defined by domains
Q <- data.timss07.G4.Qdomains
mod2 <- CDM::din( dat[,items], q.matrix=Q )
summary(mod2)

## End(Not run)

[Package CDM version 7.5-15 Index]