I am conducting a meta-analysis in psychotherapy research and want to use meta-regression to identify moderators.
The regression outcome is a correlation between a psychotherapy process variable + treatment outcome. I have 3 predictors (potential moderators) with different scales: - Study Quality (continuous) - Type of Treatment (categorial, 3 levels) - Scoring Type in primary study (binary)
I would therefore dummy code Type of Treatment (two dummy variables) and Scoring Type (one dummy variable).
And now I am a bit confused about several questions:
- Does it (statistically) make sense to conduct a "hierarchical meta-regression" testing each predictor after one another and only including it in the next step if it was relevant?
- Should I center study quality around its mean for interpretation purposes of the categorial predictors?
- Theoretically, interaction effects would be possible. They are, however, rarely included in meta-regression. Would you still think it is a good idea do so? (Even a three-way-interaction?). Plus: do I need more power to estimate the additional interaction effects with adequate stability? (I have only 22 "cases", so 3 predictors are already critical)
Thank you very much for your input, it will be greatly appreciated!