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.
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.
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.
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.
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.
1.
Select Help > Sample Data Library and open Reliability/Stability.jmp.
2.
Select Analyze > Reliability and Survival > Degradation.
3.
Select the Stability Test tab.
4.
Select Concentration (mg/Kg) and click Y, Response.
5.
Select Time and click Time.
6.
Select Batch Number and click Label, System ID.
8.
Stability Models
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.

Help created on 9/19/2017