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ERIC Number: ED428078
Record Type: Non-Journal
Publication Date: 1999-Jan-21
Pages: 51
Abstractor: N/A
Reference Count: N/A
Understanding the One-Parameter Rasch Model of Item Response Theory.
Henson, Robin K.
Basic issues in understanding Item Response Theory (IRT), or Latent Trait Theory, measurement models are discussed. These theories have gained popularity because of their promise to provide greater precision and control in measurement involving both achievement and attitude instruments. IRT models implement probabilistic techniques that yield statistics to help describe the interplay between the testing item and the respondent in terms of the unobservable latent traits that cause a given response to an item. The one-parameter IRT model, often referred to as the Rasch model, is illustrated using heuristic data. In IRT examinee ability and item difficulty estimates can be obtained that are theoretically independent of each other; therefore, that they can be used across samples of different abilities and items of varying difficulty. IRT transforms classical test theory proportions into logits, converting item difficulties and person abilities into the same linear metric across the distribution. In the Rasch model, this calibration process theoretically makes the ability statistic (theta) item-free and item difficulties ("b") examinee-free. (Contains 10 tables, 4 figures, and 9 references.) (Author/SLD)
Publication Type: Reports - Descriptive; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A