A partial least squares algorithm handling ordinal variables

Abstract

The partial least squares (PLS) is a popular path modeling technique commonly used in social sciences. The traditional PLS algorithm deals with variables measured on interval scales while data are often collected on ordinal scales. A reformulation of the algorithm, named Ordinal PLS (OrdPLS), is introduced, which properly deals with ordinal variables. Some simulation results show that the proposed technique seems to perform better than the traditional PLS algorithm applied to ordinal data as they were metric, in particular when the number of categories of the items in the questionnaire is small (4 or 5) which is typical in the most common practical situations.