I'm finally finishing a first run of all of my data! It was a steep learning curve for me, but I feel like I broke a certain part of my brain down--a barrier that never would have let this information get through normally. The specific data point is grouped with the others, and if it's normally distributed (if not, a standard transformation may make it so), a model can be used to describe the overall pattern. Anything you can think of and measure can be accounted for in the model, and you can test to see if your model is accurate. Response=treatment factors. So, you have have something like:
Stress level (measured in terms of perceived stress on a 1-10 scale) = Inborn resilience (genetic/karmic) + sleep level + exercise level (could increase or decrease it) + sleep*exercise+ sleep*genetic+ exercise*genetic+ sleep*exercise*genetic+ [other factors and interactions with those factors].
If you have precise measures for everything, you can see if there is any effect from the factors on the response (stress levels). (I wouldn't really trust anything that relied on self-reported measures though, such as the "happiness" reports). You also account for interacting factors (sleep*exercise; exercise may be less effective if sleep-deprived and sleep may be lower quality if exercise is too low, as an example). Boring but I am surprised that this sort of calculation can be done at all.
Monday, December 14, 2009
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