Randomized Item Response Models
Item responses can be masked before they are observed via a randomized response mechanism. This technique is used to protect individuals and improve their willingness to answer truthfully. Various traditional randomized response sampling techniques are discussed and extended to a multivariate setting. So-called randomized item response models will be introduced for analyzing multivariate randomized response data. This class of models can also be extended to handle explanatory information at di_erent hierarchical levels. The models discussed are particularly suitable for analyzing sensitive individual characteristics and their relationships to background variables.
KeywordsItem Response Randomize Response Cheat Behavior Item Response Model Grade Response Model
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