Hi everybody, I'm working on my PhD thesis and I need help with data analysis of longitudinal data...
To make the long story short, it's about hospital treatment of AUD. I have 3 crucial variables:
1. Self-forgiveness trait (scale)
2. Alcohol craving (scale) - longitudinal data - 3 measures/week during treatment
3. Follow up (90 days after discharge) drinking status (nominal) - 0=relapse, 1=abstinence (this one could also be measured as number of days of abstinence after discharge measured in that time point)
And I have 3 problems/hypothesis
1. Self-forgiveness trait is a predictor of changes in alcohol craving during treatment
2. Self-forgiveness trait is a predictor of drinking status 90 days after treatment
2. Changes in alcohol craving during treatment are predictor of drinking status 90 days after treatment
As you can see, my longitudinal data serves me both as criterion and predictor variable.
Is HLM best/possible way for testing my hypothesis? Should I test follow-up data with some kind of survival analysis?
|Location:||Huddersfield, West Yorkshire, UK|
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