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Table Analysis |
Often, the data represented by a contingency table represents information collected in a study on observer agreement. There may be interest in gathering information on observer error, and such a study may be done as part of testing new processes, training, or tools. Sometimes different observers are studied, and sometimes the same observer is studied at different times or under different conditions.
The members of a northeastern music association were revising their system of conducting local and state-wide high school piano competitions. Instead of using local musicians as judges, they wanted to see if they could proceed more fairly by using one of two trained judges in conjunction with local judges, with whom they needed to come to consensus. In order to see how closely the trained judges match, they did an observer agreement study using some college music students after a training session. Twenty students played one of their current pieces, and both judges rated the performance as good, skilled, or superior.
In order to analyze such data, you form the table with the ratings of one rater forming the rows of the table and the ratings of the other rater forming the columns of the table. The cells of the table are the number of students who fell into the profiles composed of the combination of both ratings. Since there are 3 outcomes, there are 9 possible combinations as represented by the cells of a two-way table. Statistics called measures of agreement are then used to assess the degree of agreement.
Figure 9.23 displays the data table containing these data. Note that the data are in frequency form, with the variable count containing the frequencies of the profile contained in each row of the table. The variable Rater1 contains the first rater's evaluations and the variable Rater2 contains the second rater's evaluations.
Figure 9.24 displays the resulting dialog.
Figure 9.25 displays the resulting Statistics dialog. Note that the chi-square tests of association and the measures of association are not appropriate for this type of table.
Note that the Tables dialog specifications (see Figure 9.5) made previously remain in effect. Therefore, both frequencies and row percentages are produced for this analysis.
Click OK in the Table Analysis dialog to perform the analysis.
Figure 9.27 contains the results for the measures of agreement.
The simple kappa coefficient has a value of 0.4697, with a 95 percent confidence bounds of (0.1566, 0.7828). This suggests modest agreement of ratings. Note that the Bowker's test of symmetry is also printed; this is a test that the probabilities represented by a square table satisfy symmetry.
When you have a 2 × 2 table, the measure of agreement produced is McNemar's test.
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