Document Type

Presented Paper

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publication Date

4-2004

Abstract

In this simulation study, data were generated such that some items fit the generalized partial credit model (GPCM) while other items fit the nominal response model (NRM) but not the constraints of the GPCM. The purpose was to explore (a) how the errors in parameter estimation were affected by using the GPCM when the constraints of the GPCM were inappropriate, and (b) how the errors were affected by using the less-constrained NRM when the constraints of the GPCM were appropriate. With large sample sizes, there were considerable gains in precision from using the NRM when the GPCM was inappropriate, and only small losses in precision from using the NRM when the GPCM would have been appropriate. With small samples, there were greater benefits due to applying the constraints of the GPCM when appropriate, and smaller benefits due to using the NRM when the GPCM was inappropriate.

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