Im running a study that tests whether an intervention is effective in reducing depression levels, increasing well-being, optimism and self-esteem and increasing positive affect. My DV's are: Depression, Well-being, Optimism, Self-Esteem, Positive/Negative affect. my iv is the intervention itself.
There are 62 participants in the Pre-assessment condition and 70 participants in the post-assessment condition however its a within sample.
which statistical analysis should i use? A T-test or Anova?
With this data alone you will be unable to do any meaningful analysis of whether the intervention is effective.
You would need something that would tell you what would have happened, if the intervention had not been given. Patients will typically improve even in the absence of an intervention due to regression to the mean (especially if a certain patient state was required for entry), the placebo effect, the Hawthorne effect, more attention being paid to them as part of a study and so on.
Ideas for making some valid conclusions could be using historical controls (e.g. using the robust meta-analytic predictive approach or power prior approaches), concurrent controls (e.g. using propensity score methods, especially if you compare versus another intervention so that both interventions get a placebo effect) and other methods for observational studies.
