IRT model fit from different perspectives

Abstract

Item response theory (IRT) is a collection of statistical models that used for development, evaluation, and scoring of instruments. IRT models describe, in probabilistic terms, the relationship between a person's response to a test item and his or her standing on the construct being measured by the test. These measured constructs include any latent (i.e., unobservable) variable, such as depression, achievement, or attitude, that requires multiple test items to estimate a person's level on the construct. The properties of these models offer many well-known advantages in testing applications. However, the extent to which these properties are attained is dependent on the degree to which the IRT model itself is appropriate. This thesis is concerned with evaluation of model fit from two perspectives: the items and the respondents.