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Longitudinal data analysis - is HLM best choice for my data?

Hi everybody, I'm a Clinical Psychologist working on my PhD thesis and I need help with data analysis of longitudinal data...


To make the long story short 8 (it's actually a metacognitive story...), it's about hospital treatment of AUD (Alcohol Use Disorder). I have 3 crucial variables:

1. Self-forgiveness trait (scale)
2. Alcohol craving (scale) - longitudinal data - 3 measures/week during treatment (cca 2-3 months)
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

Is HLM best/possible way for testing my hypothesis? Should I test my follow-up data with some kind of survival analysis?

Thanks in advance,

Nikola

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