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 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.
Open the Stability.jmp data table in the Reliability folder of Sample Data.
2.
Select Analyze > Reliability and Survival > Degradation.
3.
Select Concentration (mg/Kg) and click Y, Response.
4.
Select Time and click Time.
5.
Select Batch Number and click Label, System ID.
6.
Select Stability Test from the Application menu.
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.