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“Don’t know” and “not applicable” response options commonly appear in educational research. Completely ignoring these responses or treating them as missing data may lose information and cause measurement bias, especially when the non-responses actually correlate to the underlying trait of measurement. This study proposes a semi-model to directly incorporate such non-responses into the estimation of the latent trait. This model was developed based on the nested relationship between generalized partial credit model and nominal response model. Also, an applied study was conducted and ensured that the new model can provide valid information of person and item parameters.
Sherry Zhou, University of Florida
Anne Corinne Huggins-Manley, University of Florida
James Algina, University of Florida