Methods for incorporating ordinal assumptions into the analysis of the means ofktreatments (k>2) are critically reviewed. These methods are examined under three headings: (1)Global: statistics that give an overall assessment of the presence of a trend in the data (e.g. linear and isotonic regression); (2)Multiple comparisons: statistics based on the repetition (explicit or implicit) of comparisons between pairs of treatments; (3)Joint probability: two statistics are computed, one giving an overall assessment of the differences between the means, the other assessing the specifically ordinal information in the data; the joint significance level of these two statistics is then determined. Numerical examples of all the methods are provided.