My research scenario is as follows:
I have ppts in three different intervention groups (independent variable one, between groups)
I have two time points (independent variable two, within groups) where scores on psychometrics will be recorded first at month 0 and month 12
My dependent variable is treatment change from month 0 to month 12
Am I right in thinking that the appropriate statistical analysis would be a mixed factorial ANOVA? As I have two IV's, one between, one within, and want to measure their effect both together and separately on my DV.
It took me a while to work out that ppts = participants.
I have two questions (for now):
1) Were participants randomly allocated to the 3 groups?
2) Was the baseline score (at time 0) obtained prior to the interventions being administered?
If the answer is yes to both of those questions, then I think ANCOVA would be in order (with the 12-month score as the DV and the baseline score as the covariate). See this BMJ Stats Note, for example:
Article Statistics Notes: Analysing controlled trials with baseline ...
https://www.bmj.com/content/323/7321/1123.long
HTH.
IYH Dear Georgie East
Kindly see q/a w my free AI LLM statistics bot https://hf.co/chat/r/ACjLUQq
In short: Yes, your proposed statistical analysis using a mixed factorial ANOVA seems appropriate given your research setup. Choosing either mixed factorial ANOVA or ANCOVA depends on your research goals and priorities. While ANCOVA focuses primarily on comparing the adjusted post-treatment scores, controlling for the baseline variation, the mixed factorial ANOVA investigates the main and interaction effects involving both the intervention groups and the temporal component.
You say "My dependent variable is treatment change from month 0 to month 12." Just to be clear, do you mean score12 - score0, or are you conceptualizing change in some other way? Do you believe that someone who starts with a low score at time 0 and goes up 5 points is the same improvement as someone near the top at time 0?
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