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  1. Jul 16, 2020 · Item characteristic curves are often presented in Rasch articles and presentations; however, how should researchers read such curves and look at such curves to better evaluate test or survey items? What is the pattern that researchers want to see from data that are...

    • William J. Boone, John R. Staver
    • 2020
  2. An Item-Characteristic Curve, pi, = probability that a test taker with trait value θ passes item i. A steep ICC indicates that the item discriminates well, a shallow slope, that it discriminates poorly. Also, an ICC provides bi an index of item difficulty that increases, rather than decreases, with difficulty.

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  4. It increases until at the highest levels of ability, the probability of correct response approaches 1. This S-shaped curve describes the relationship between the probability of correct response to an item and the ability scale. In item response theory, it is known as the item characteristic curve. Each item in a test will have its own item ...

    • 176KB
    • 16
  5. It was first used as a model for the item characteristic curve in the late 1950s and, because of its simplicity, has become the preferred model. The equation for the two-parameter logistic model is given in equation 2-1 below. θ = 1 = 1. ( ) + e −. L. + e −. ( θ − b ) [2-1] where: e is the constant 2.718.

    • 250KB
    • 26
  6. Item Characteristic Curve. The item characteristic curve (ICC) is the fundamental unit in IRT and can be understood as the probability of endorsing an item (for a dichtomous response) or responding to a particular category of an item (for a polytomous response) for individuals with a given level of the attribute.

  7. Apr 26, 2017 · The item characteristic curve will be displayed on the screen by typing in the following command line: > icc(b=-2.0, a=1.0, c=.10) (d) The item characteristic curve is located in the low-ability end of the scale and it is moderately steep. (e) Next, we want to put another item characteristic curve on the same graph. Type in the following ...

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