Data - Attribute Agreement Analysis
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Data can be text or numeric. The assigned ratings can be nominal or ordinal:

·    Nominal data are categorical variables that have two or more levels with no natural ordering. For example, the levels in a food tasting study may include crunchy, mushy, and crispy.

·    Ordinal data are categorical variables that have three or more levels with a natural ordering, such as strongly disagree, disagree, neutral, agree, and strongly agree.

If the response is a text column and the data are ordinal, use Editor > Column > Value Order to define a nonalphabetical ordering on the text values.

Data can be stacked in an attribute column or unstacked in multiple columns. For attribute column data, stack all of the responses in one column and set up grouping indicator columns for the appraiser and part number. The grouping indicators define each sample. Grouping indicators and responses can be text or numeric. For multiple column data, responses for each appraiser and each trial are in separate columns.

Here is the same data set structured both ways:

Attribute column data                 

Sample

Appraiser

Response

1

A

Good

1

A

Good

1

B

Bad

1

B

Good

2

A

Good

2

A

Good

2

B

Good

2

B

Good

3

A

Bad

3

A

Good

3

B

Bad

3

B

Bad

4

A

Good

4

A

Good

4

B

Good

4

B

Good

5

A

Bad

5

A

Bad

5

B

Good

5

B

Bad

Multiple columns data

Sample

Appraiser A - Trial 1

Appraiser A - Trial 2

Appraiser B - Trial 1

Appraiser B -Trial 2

1

Good

Good

Bad

Good

2

Good

Good

Good

Good

3

Bad

Good

Bad

Bad

4

Good

Good

Good

Good

5

Bad

Bad

Good

Bad

Note

When your data are in multiple columns, you must enter the trials for each operator together, as shown above. The order of the trials must be the same for each operator.