On the High Predictive Potential of Change and Growth Measures

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Abstract
Formulas in the statistical theory of test scores have led some psychometricians to believe that measures of change and growth have questionable value in research. However, certain combinations of parameters, when substituted into these formulas, yield reliable change scores and high non-spurious correlations between change scores and independent criterion scores, even when pretest scores are not good predictors of either changes or the criterion. Because of mathematical constraints, these particular combinations of parameters are the ones to be expected in research designs if valid and reliable changes in individuals' test scores do occur. Accordingly, it is possible for measures of change and growth to have excellent predictive value, as investigators in many fields have taken for granted, and, conversely, independent variables can be excellent predictors of changes. Although criteria which are highly correlated with changes are difficult to discover empirically, their existence cannot be ruled out by statistical arguments alone.

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