GMAT {difNLR}

Dichotomous dataset based on GMAT with the same total score distribution for groups.

Description

The GMAT is a generated dataset based on parameters from Graduate Management Admission Test (GMAT, Kingston et al., 1985). First two items were considered to function differently in uniform and non-uniform way respectively. The dataset represents responses of 2,000 subjects to multiple-choice test of 20 items. A correct answer is coded as 1 and incorrect answer as 0. The column group represents group membership, where 0 indicates reference group and 1 indicates focal group. Groups are the same size (i.e. 1,000 per group). The distributions of total scores (sum of correct answers) are the same for both reference and focal group (Martinkova et al., 2017). The column criterion represents generated continuous variable which is intended to be predicted by test.

Usage

data(GMAT)

Format

A GMAT data frame consists of 2,000 observations on the following 22 variables:

Item1-Item20

dichotomously scored items of the test

group

group membership vector, "0" reference group, "1" focal group

criterion

continuous critetion intended to be predicted by test

Author(s)

Adela Hladka (nee Drabinova)
Institute of Computer Science of the Czech Academy of Sciences
Faculty of Mathematics and Physics, Charles University
[e-mail]

Patricia Martinkova
Institute of Computer Science of the Czech Academy of Sciences
[e-mail]

References

Kingston, N., Leary, L., & Wightman, L. (1985). An exploratory study of the applicability of item response theory methods to the Graduate Management Admission Test. ETS Research Report Series, 1985(2): 1–64.

Martinkova, P., Drabinova, A., Liaw, Y. L., Sanders, E. A., McFarland, J. L., & Price, R. M. (2017). Checking equity: Why differential item functioning analysis should be a routine part of developing conceptual assessments. CBE–Life Sciences Education, 16(2), rm2, doi:10.1187/cbe.16-10-0307.

See Also

GMATtest, GMATkey