Nested Logit Models for Multiple-Choice Item Response Data

作者：Suh Youngsuk^*; Bolt Daniel M

来源：Psychometrika, 2010, 75(3): 454-473.

DOI：10.1007/s11336-010-9163-7

• Multiple-choice items
• multiple-choice models
• nested logit models
• nominal response model
• marginal maximum likelihood estimation
• item information
• distractor selection information
• distractor category collapsibility

Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all distractor categories, making it easier to allow decisions about including distractor information to occur on an item-by-item or application-by-application basis without altering the statistical form of the correct response curves. Marginal maximum likelihood estimation algorithms for the models are presented along with simulation and real data analyses.

• 出版日期2010-9