These are tests of general association , where the null hypothesis is that the row and column variables are independent and alternative hypotheses is simply that the row and column variables are associated. The outcome reflects whether individuals showed no improvement, some improvement, or marked improvement. Here, the outcome variable is an ordinal one, and it is probably important to determine if the relation between treatment and outcome is the same for males and females. The output begins with the frequency table, including row percentages. The results for the chisq option is shown below.
All tests show a significant association between treatment and outcome.
Tests which take the ordinal nature of a variable into account are provided by the cmh option on the tables statement. They generally have higher power when the pattern of association is determined by the order of an ordinal variable. Mean score differences . If the column variable is ordinal, assigning scores to the column variable produces a mean for each row. The association between row and column variables can be expressed as a test of whether these means differ over the rows of the table, with r - 1 df.