Three related methods for assigning interval scale values to a set of ordered categories are proposed, based on the assumption that certain patterns of linear regressions exist among a set of variables. Technique I requires that the second administration of a variable be a linear function of the first. Technique II requires that two variables each be linear functions of one another (“symmetric linearity”). Technique III requires at least three linear regressions among three variables. The category values that are consistent with the assumed patterns of linear regressions are unique up to a linear transformation.