KB36.1PL: Difficulty parameter estimates for KB36 data under a 1PL...

In SNSequate: Standard and Nonstandard Statistical Models and Methods for Test Equating

Difficulty parameter estimates for KB36 data under a 1PL model

Description

This data set contains the estimated item difficuty parameters for the KB36 data, assuming a 1PL model. Two sets of parameters estimates for test forms X and Y are available: one that results from a fit assuming the traditional logistic link, and one which comes from the fit using a cloglog (asymmetric) link.

Usage

data(KB36.1PL)

Format

A list of 2 elements containing item (difficulty) parameters estimates for test forms X and Y under the logistic-link model (b.logistic), and under the cloglog-link model (b.cloglog)

Details

This data set is used to illustrate the characteristic curve methods (Haebara and Stocking-Lord) which can use an asymmetric cloglog ICC for the calculations, as described in Estay (2012).

A 1PL model using both logistic and cloglog link can be fitted using the lmer() function in the lme4 R package (see De Boeck et. al, 2011 for details).

Source

The item parameter estimates for the 1PL model with logistic link are also shown in Table 6.13 of Kolen and Brennan (2004).

References

De Boeck, P., Bakker, M., Zwitser, R., Nivard, M., Hofman, A.,Tuerlinckx, F., Partchev, I. (2011). The Estimation of Item Response Models with the lmer Function from the lme4 Package in R. Journal of Statistical Software, 39(12), 1-28.

Kolen, M., and Brennan, R. (2004). Test Equating, Scaling and Linking. New York, NY: Springer-Verlag.

Estay, G. (2012). Characteristic Curves Scale Transformation Methods Using Asymmetric ICCs for IRT Equating. Unpublished MSc. Thesis. Pontificia Universidad Catolica de Chile

Examples

data(KB36.1PL)
## maybe str(KB36.1PL) ; plot(KB36.1PL) ...

SNSequate documentation built on Dec. 28, 2022, 1:35 a.m.