Hi everyone!
I'm doing a PhD in Clinical Psychology and I have some treatment data to analyse. The design is a 2 (condition: self-compassion, cognitive restructuring) x 5 (time: baseline, mid-treatment, post-treatment, 1-week follow-up, and 5-week follow-up) design. I had 119 participants randomized and engage in their respective interventions for a 2-week period, with follow-up assessments. The aim was to reduce social anxiety.
One analysis I'm trying to do is mediation, and preferably I would use a more simple strategy such as Hayes' PROCESS macro on SPSS. However, my understanding is that I won't be able to use all five waves of my data if I use PROCESS. Does anyone know if that is an appropriate strategy for multiple waves? Should I be using all information? And if so, how?
I feel your data suggest a factorial setup of experiment. So,analysis combining both factors may show u main effect and interaction effect to choose significant factor or interaction effects suitably.
Jeremy,
it seems to me your design is too complex for PROCESS to handle.
If you expect social anxiety to follow a specific trend, you could try a (piece-wise) latent growth model. If not, I would suggest a latent change score model.
See:
Article Longitudinal Analysis in Occupational Health Psychology: A R...
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