Sum Scores of Behavioral Scales: A Note on an Observed Distribution Extension

A recent discussion of potentially serious drawbacks of the widely used scale sum scores is extended to nonnormal observed variables, and a didactic discussion is provided of their underpinnings. It is pointed out that the possibly marked bias and mean squared error as well as parameter estimator inconsistency, which result if using the sum scores as predictors of response measures, are not limited to normally distributed manifest variables. The asymptotically distribution-free estimation approach within the structural equation modeling framework is recommended to consider with large samples and nonnormal observed measures, in lieu of the common and traditional application of the scale sum scores as predictors of outcome variables. The approach is demonstrated in empirically relevant settings with substantially nonnormal data, where it is found to decidedly outperform that frequent application of the popular sum scores.