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Stability Analysis Course - commercial batches
Hello everyone,
I am taking a Stability Analysis Course of JMP
(https://community.jmp.com/t5/Stability-Analysis/Stability-Analysis-Course/ta-p/703300)
in order to perform a stability data analysis and identify trends.
In one of the course exercises, I came across a table (Attached to the message) that includes columns for slope and confidence/ tolerance interval boundaries. I would like to create similar columns for my own table.
I would appreciate any help—how can I generate these columns?
It looks like they were not created using a formula.
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Re: Stability Analysis Course - commercial batches
Look at the bottom of the course journal. There are scripts that generalize the functionality of some of the course demonstrations to work with your data. Your data tables should conform to the expected data columns and formats.
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Re: Stability Analysis Course - commercial batches
Thank you very much for your response.
If I understand correctly, if I want to create such columns myself, it is not possible without knowing how to write in JSL...
I used the script, but since not all intervals were tested in some batches, the script did not run properly on all the data.
Do you know a good way to analyze trends for products undergoing stability testing (in the pharmaceutical field)?
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Re: Stability Analysis Course - commercial batches
You do not need a script to create a data table. There is no requirement that all the batches have the same number of time points, but there is likely a minimum number to support fitting the models.
Regression analysis is the usual way to analyze trends. It is not the only way, but it is flexible and realistic for most cases. You can use Analyze > Fit Y by X to launch the Bivariate platform for trend analysis.
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Re: Stability Analysis Course - commercial batches
Hi @Bar2024 : The stability platform is designed "to analyze trends for products undergoing stability testing (in the pharmaceutical field)" based on ICH Q1E. From a statistical perspective, it is the same as the model you'd fit via Fit Model with Batch, Time, and Batch*Time as effects, and then reducing the model as described in Q1E with alpha = 0.25 as a threshold for statistical significance.
https://www.jmp.com/support/help/en/18.1/index.shtml#page/jmp/example-of-stability-analysis.shtml#