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Calibration of psychological measures: An illustration of three quantitative methods

Patrick E. McKnight

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Abstract

The scores or metrics from psychological measures are rarely interpretable. Uninterpretable metrics result in poorly understood psychological research findings. In response to this problem, several methods are proposed that render metrics more meaningful. The methods employed are calibration procedures. Three calibration procedures are illustrated that prove to be extremely powerful in making the metrics of two related measures more understandable. Establishing the behavioral implications of the scores, computing just noticeable differences, and calibrating between measures are the three procedures described and illustrated. For the purposes of illustration, two measures of Attention Deficit Hyperactivity Disorder (ADHD) are used in the calibration procedures. These two measures are often used interchangeably without regard to their relationship with one another. The three procedures and the results of each are discussed in detail.

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What this paper is about

The scores or metrics from psychological measures are rarely interpretable. Uninterpretable metrics result in poorly understood psychological research findings. In response to this problem, several methods are proposed that render metrics more meaningful. The methods employed are calibration procedures. Three calibration procedures are illustrated that prove to be extremely powerful in making the metrics of two related measures more understandable. Establishing the behavioral implications of the scores, computing just noticeable differences, and calibrating between measures are the three procedures described and illustrated. For the purposes of illustration, two measures of Attention Deficit Hyperactivity Disorder (ADHD) are used in the calibration procedures. These two measures are often used interchangeably without regard to their relationship with one another. The three procedures and the results of each are discussed in detail.

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Available abstract

The scores or metrics from psychological measures are rarely interpretable. Uninterpretable metrics result in poorly understood psychological research findings. In response to this problem, several methods are proposed that render metrics more meaningful. The methods employed are calibration procedures. Three calibration procedures are illustrated that prove to be extremely powerful in making the metrics of two related measures more understandable. Establishing the behavioral implications of the scores, computing just noticeable differences, and calibrating between measures are the three procedures described and illustrated. For the purposes of illustration, two measures of Attention Deficit Hyperactivity Disorder (ADHD) are used in the calibration procedures. These two measures are often used interchangeably without regard to their relationship with one another. The three procedures and the results of each are discussed in detail.

Key concepts: Calibration, Computer science, Psychology, Statistics, Mathematics

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