In almost all applications of measurement there is some sort of response by a human subject. Almost always, the response scale is ordinal, but almost always it is treated as if it were an interval measure. Methods for treating data ordinally are currently being developed in three areas: ordinal analysis for questionnaire responses, ordinal approaches to multiple regression, and an ordinal true score theory. Each of these areas is discussed in detail. In all of them, a major concern has been to stay as close as possible to the form in which the data are presented. When the data are dichotomous, statistics are used that measure the degree of agreement with the least distortion due to extraneous factors. Least squares statistics are avoided as a criterion of fit whenever possible. Kendall's tau, or one of its variations, is used as a measure of correlation. While success is not complete in these ordinal data analysis methods, there is enough of it to suggest that it could be extensive. (BW)