The effect of alternative scoring methods on the analysis of rank order categorical data

The purpose of this article is to examine the effects of five univariate scoring techniques for rank order categorical data and the results of analyses using each of the techniques for five‐ and ten‐point bi‐polar adjective scales. The effect of scoring method and scale length is assessed for the resultant distance to multivariate normality, inter‐item reliability, discriminant analysis, least squares regression and logistic regression. For these data, the strongest effect of scoring was on distance to multivariate normality and determination of significant variables.

Notes

Linda L. Golden is Professor of Marketing and Patrick L. Brockett is Professor of Finance. Both are at the University of Texas at Austin. We thank the anonymous referrees for their helpful comments.