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Introduction Rasch User’s Group

Introduction Rasch User’s Group. Peer Tymms MMXI. Outline. The day The unique nature of Rasch Unidimensionality Using probabilities. Rasch model. P is the probability of someone of proficiency theta getting an item correct. Item characteristic curve. Item characteristic curve. b = -1.

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Introduction Rasch User’s Group

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  1. IntroductionRasch User’s Group Peer Tymms MMXI

  2. Outline • The day • The unique nature of Rasch • Unidimensionality • Using probabilities

  3. Rasch model P is the probability of someone of proficiency theta getting an item correct

  4. Item characteristic curve

  5. Item characteristic curve b = -1 b = 1

  6. Key Points • Item characteristics are not group dependent. • Scores describing examinees’ abilities are not test dependent. • A measure of precision for each ability score is produced. • The probability that an examinee of any ability will answer items of any difficulty correctly is estimated.

  7. The two parameter model

  8. Item characteristic curve a = 2 a = 0.5

  9. The three parameter model

  10. Item characteristic curve

  11. Wright If measurement is our aim, nothing can be gained by chasing extra item parameters like c and a. Only the Rasch process can maintain units that support addition and so produce results that qualify as fundamental measurement.

  12. Linacre allowing or parameterising discrimination or guessing, which are sample-dependent indices, limits the meaning of the measures to just that subset of items and persons producing these particular data.

  13. Modelling or measuring? The Rasch approach seeks to make the data fit the model not to make the model fit the data. Andrich (after Kuhn) notes that in scientific revolutions the old guard never hear what the revolutionaries say.

  14. Unidimensionality Andrich suggests a fractal perspective

  15. All knowledge General & academic knowledge Science Sport Music History Physics Biology Chemistry Organic Physical Mechanisms inorganic

  16. Using probabilities

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