A method for handling correlated explanatory variables in the context of a multiple regression model. In PLS the first stage is to determine k uncorrelated variables that are linear combinations of the explanatory variables. The combinations are chosen for their predictive ability. Principal components regression analysis uses a different technique to achieve the same objective.