GMAT2test: Dataset based on GMAT.

In drabinova/difNLR: DIF and DDF Detection by Non-Linear Regression Models

Dataset based on GMAT.

Description

The GMAT2test 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 data set represents responses of 1,000 subjects to multiple-choice test of 20 items. Aditionally, 4 possible answers on all items were generated, coded A, B, C, and D. The column group represents group membership, where 0 indicates reference group and 1 indicates focal group. Groups are the same size (i.e. 500 per group).

Usage

data(GMAT2test)

Format

A GMAT2test data frame consists of 1,000 observations on the following 21 variables:

Item1-Item20

nominal items of the test coded A, B, C, and D

group

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

Correct answers are presented in GMAT2key data set.

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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1187/cbe.16-10-0307")}.

See Also

GMAT2, GMAT2key

drabinova/difNLR documentation built on Feb. 2, 2024, 7:14 p.m.