Attribute Agreement Analysis
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Stat > Quality Tools > Attribute Agreement Analysis

Use attribute agreement analysis to assess the agreement of nominal or ordinal ratings given by multiple appraisers. The measurements are subjective ratings by people rather than direct physical measurements. Examples include:

·    Automobile performance ratings

·    Classification of fabric quality as "good" or "bad"

·    Ratings of wine color, aroma, and taste on a 1 to 10 scale

In these situations, quality characteristics are difficult to define and assess. To obtain meaningful classifications, more than one appraiser should classify the response measure. If the appraisers agree, the possibility exists that the ratings are accurate. If the appraisers disagree, rating usefulness is limited.

Note

Attribute Agreement Analysis was previously called Attribute Gage R&R Study in Minitab Release 13. Attribute Agreement Analysis, a technique to assess appraisers' agreement, is different from Attribute Gage Study (Analytic Method), a method to examine the bias and repeatability of an attribute measurement system.  

Dialog box items

Data are arranged as

Attribute column: Choose to enter the column containing the responses.

Samples: Enter the column containing the sample or part number.

Appraisers: Enter the column containing the appraiser name or number.

Multiple columns (Enter trials for each appraiser together): Choose to enter the columns containing the responses. Keep the  trials for each appraiser in adjoining columns.

Number of appraisers: Type the number of appraisers.

Number of trials: Type the number of trials.

Appraiser names (optional): Type the appraisers' names or enter a column of names.

Known standard/attribute (optional): Enter a column containing the attribute or known standard for each sample. The column can contain either numeric or text attributes, but the data type needs to match the response type.

Categories of the attribute data are ordered: Check to specify that the data have more than two levels and are ordinal.

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