Presentation paper

The effect of nonignorable missing data in computerized adaptive test on item fit statistics for polytomous item response models


By: Shudong Wang, Hong Jiao


For both linear and adaptive tests, it is crucial to evaluate model-data fit because the goodness-of-fit of item response theory (IRT) models are relevant to any purpose of a test. To date, all item fit statistics are derived based on linear tests and almost all studies have been done in the context of linear testing. These studies are conducted based on assumptions under regular conditions for fixed test forms, such as no missing responses and normal distribution of unidimensional ability for a population.

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