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If the p-value is less than 0.25, the slopes are assumed to be different across batches. The procedure stops and Model 1 is used to estimate the expiration date.
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If the p-value is greater than or equal to 0.25, the slopes are assumed to be common across batches. The procedure continues to step 2.
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If the p-value is less than 0.25, the intercepts are assumed to be different across batches, and Model 2 is used to estimate the expiration date.
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If the p-value is greater than or equal to 0.25, the intercepts are assumed to be common across batches, and Model 3 is used to estimate the expiration date.
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Consider the Stability.jmp sample data table. The data consists of product concentration measurements on four batches. A concentration of 95 is considered the end of the product’s usefulness. Use the data to establish an expiration date for the new product.
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Select the Stability Test tab.
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Click OK.
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The test for equal slopes has a p-value of 0.8043. Because this is larger than a significance level of 0.25, the test is not rejected, and you conclude the degradation slopes are equal between batches.
The test for equal intercepts and slopes has a p-value of <.0001. Because this is smaller than a significance level of 0.25, the test is rejected, and you conclude that the intercepts are different between batches.