A Comparison of the Recovery of Parameters Using the Nominal Response and Generalized Partial Credit Models
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.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
DeMars, C. E. (2004, April). A comparison of the recovery of parameters using the nominal response and generalized partial credit models. Poster presented at the annual meeting of the American Educational Research Association, San Diego