I'm currently working with a data set that includes multiple variables associated with each of 10 years of data. The basic structure, with (example hypothetical) variables in caps, is from YEAR to year, TV WATCHING increased, which led to less HAPPINESS and less SLEEP.
I want to test whether TV watching increased as time went on, and whether those increases led to a decrease happiness and sleep. I have found a statistically significant positive correlation between YEAR and TV WATCHING, and a significant negative correlation between TV WATCHING and HAPPINESS/SLEEP. But I would like to do a more sophisticated analysis.
Please let me know what you feel would make the most sense. I'm thinking I could do a multivariate regression with TV WATCHING as the single IV and HAPPINESS/SLEEP as the two DVs. But I'm not sure how robust that would be, plus it ignores the time element. So then I was thinking structural equation modeling with YEAR -> TV WATCHING -> HAPPINESS; SLEEP. But I wasn't sure that was the best approach either.
Any assistance will be much appreciated. Thanks!