Calculating the test-retest reliability co-efficient from normative retest data for determining reliable change.

This letter is essentially an addendum to Hinton-Bayre (2010), where a comparison of several models of reliable change (RC) was made. RC statistics have been developed to assess whether an individual has demonstrated statistically significant change over time or following an intervening event or treatment. Popular settings for this include sports-related concussion, brain surgery, and cardiac surgery. The more unique element of this methodology is the ability to compare preand postmeasurements. There is a growing amount of test-retest normative data available to the clinician to assess whether an individual’s change is more than would be expected due to chance. Hinton-Bayre (2010) demonstrated that all currently popular RC models can be conceptualized by a fundamental expression, RC 1⁄4 (Y Y′)/SE, where Y is the actual retest score, Y′ the predicted retest score, and SE the associated standard error. Contemporary RC models estimate the Y′ and SE differently. There is ongoing evaluation of the most appropriate RC model(s) (Maassen, Bossema, & Brand, 2009). Hinton-Bayre (2010) went on to demonstrate that most RC models can be calculated with the possession of simple test-retest statistics taken from a relevant control group, particularly, the initial test and retest means and standard deviations, and the test-retest reliability. Most papers will report means and standard deviations. However, it is less common for the reliability coefficient to be presented. In a two-point situation (test and retest), with the possession of an inferential statistic (viz. repeated measures tor F-test), and using some simple algebra, the following expression can be used to determine the test-retest reliability coefficient.