Purpose

    The Cochran Q test is an extension of McNemar's Chi-square test for changes  in frequencies or proportions to k (more than two) dependent samples. Specifically, it tests whether several matched frequencies or proportions differ significantly among themselves.

Preparations

    Run Statistics→Nonparametric Statistics →Cochran Q Test.... command. The test assumes that the variables are coded as 1's and 0's.

Results

    The Cochran Q test only requires a nominal scale, or that the data have been artificially dichotomized. A typical example where the Q test is useful is when you want to compare the difficulty of dichotomous questionnaire items that can either be answered right or wrong. Here, each variable in the data file would represent one item, and contain 0's (wrong) and 1's (right). If the Q test is significant, then we conclude that the items are of different difficulty since different items were answered correctly by more or fewer respondents.