Linear regression with two measurement points?

JdjfjkdsnByJdjfjkdsn

Hello everyone,

I want to calculate linear regressions and mediations. I collected my two AVs at two measurement points, T1 and T2 (with a stimulus in between).

Using paired samples t-tests, I saw that there was a significant difference for one of my AVs, but not for my other AV.

Now I want to determine whether a variance factor (UV), which I only collected at T2, can explain the influence of the stimulus on the two AVs (linear regression is used for this). To learn more about the influence of the UV on the two AVs, there are mediation analyses that examine the influence of a mediator closely related to the variance factor.

Is there a way to include the T1 values ​​in Jamovi's linear regressions and mediations to find out more about the difference? Is this only possible for the AV, where I also observed the difference?

I really hope you understand what I mean 🙂

I am very grateful for help

Best regards

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LUKEars
LUKEars
9 months ago

So “Linear Regression” I actually know more when one assumes a linear relationship between two measurements…

Example 1: A bird on the air-cushion runway… Uniform movement… Measuring size 1: Time from passing through the light barrier A to passing through the light barrier B….

Your example: I don’t know exactly what measured values you have now… is (T2-T1) always the same for each measurement? or what connection do you think?

Example 2: If you accelerate the waking with a rope to which a falling weight is attached, then you realize that it is no longer a linear relationship… so you suspect that it may be a square relationship… i.e. a linear relationship between “measuring size 1” and “measuring pitch 2”….

do you have a guess about your system, what is linear?

if an AV does not change through the stimulus, then does it have nothing to do with the experiment?

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