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The advantages of using person location estimates from the Rasch model over raw scores for the measurement of change using a common test include the linearization of scores and the automatic handling of statistical properties of repeated measurements. However, the application of the model requires that the responses to the items are statistically independent in the sense that the specific responses to the items on the first time of testing do not affect the responses at a second time. This requirement implies that the responses to the items at both times of assessment are governed only by the invariant location parameters of the items at the two times of testing and the location parameters of each person each time. A specific form of dependence that is pertinent when the same items are used is when the observed response to an item at the second time of testing is affected by the response to the same item at the first time, a form of dependence which has been referred to as response dependence. This paper presents the logic of applying the Rasch model to quantify, control and remove the effect of response dependence in the measurement of change when the same items are used on two occasions. The logic is illustrated with four sets of simulation studies with dichotomous items and with a small example of real data. It is shown that the presence of response dependence can reduce the evidence of change, a reduction which may impact interpretations at the individual, research, and policy levels.
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Innovative Measurement Approaches to Optimise the Comparability of Large Scale & High Stakes Performance Assessment
1/01/14 → 31/12/16