Precision and Sample Size Requirements for Regression-Based Norming Methods for Change Scores
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To interpret a person’s change score, one typically transforms the change score into, for example, a percentile, so that one knows a person’s location in a distribution of change scores. Transformed scores are referred to as norms and the construction of norms is referred to as norming. Two often-used norming methods for change scores are the regression-based change approach and the T Scores for Change method. In this article, we discuss the similarities and differences between these norming methods, and use a simulation study to systematically examine the precision of the two methods and to establish the minimum sample size requirements for satisfactory precision.
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2012 ◽
Vol 49
(3-4)
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pp. 147-160
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2017 ◽
Vol 267
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pp. 012029
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2019 ◽
Vol 2673
(3)
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pp. 24-43
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2006 ◽
Vol 2
(3)
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pp. 31-45
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