Normalize across trials using controls

thestrider — Tue, 16 Sep 2025 02:06:32 GMT

I have a datasets of populations with a response. I triplicated the experiment, so I have 3 trials of data, but the response rate likely varies between trials. It is a hypoxia response rate, which is sensitive to things like humidity/temperature that I can't perfectly control.

Each trial consists of a population with different treatments, plus empty vector controls.

So like this, but with like 50 entries for each treatment/control per trial:

Trial Response

1 TreatmentX 999

1 Control 576

2 TreatmentX 1111

2 Control 700

3 TreatmentX 700

3 Control 350

So for this example the treatment is always above control, but control varies alot. I was thinking of using Dunnetts test to see which treatments are different from control, but I want to normalize the data to account for the trial day differences. The population sizes vary so I can't just use the total average for each day, but I should be able to use my controls to normalize each trial. How do I do this in JMP?

Re: Normalize across trials using controls

hogi — Tue, 16 Sep 2025 06:15:23 GMT

If it's just about calculating the ratio (or difference) per trial , you can use the Normalization AddIn from https://marketplace.jmp.com/appdetails/Normalization+GUI

e.g. with the settings:

- column to normalize : Response

- function: ratio or difference

- grouping: by trial

- subset: Control

[The default aggregation is median, which works well even with just a single control and is much faster than the other modes.]

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Normalize across trials using controls

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