Attribute Gage Study (Analytic Method) Overview
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Attribute gage studies assess the amount of bias and repeatability of a gage when the response is a binary attribute variable. Unlike a variable gage, an attribute gage does not give information on the quality of a part but only indicates whether a part is accepted or rejected based on a set of specified standards.

Attribute gage study results depend heavily on the way you select the parts and the number of runs performed on each part. You should select the parts at nearly equidistant intervals and know the reference value for each selected part. The number of required runs performed on each part depends on the method you use to test the bias of the gage. Minitab offers two methods to test whether the bias is zero: AIAG and regression. If you use AIAG (default), you must have at least 20 trials per part. The minimum number of trials necessary to use the regression method is 15. However, 20 or more trials are recommended. See Data - Attribute Gage Study (Analytic Method) for more information on the data requirements.

Minitab calculates the bias and repeatability of the gage using the method described in [1]. Because no actual measurements from the gage are available to estimate bias and repeatability, Minitab calculated bias and repeatability by fitting the normal distribution curve using the calculated probabilities of acceptance and the known reference values for all parts.