I am doing a meta-analysis and am looking for some guidance on which statistical test will help me do the following.
I want to understand the effect size a treatment has on a population. There are articles published that have an experimental sample with treatments A and B as well as a control group. There are articles published with a sample with treatment A and the control group. I want to understand the effect that treatment B has by comparing the findings in these articles.
I thought this was a case of a random effects situation because the populations sampled are similar but cannot be assumed to be exactly the same.
I would love some help with figuring out which statistical test best fits to answer this question.
Additional info:
Both treatments are binary values: For treatment A either you have a male or female sex for example (none of the data in the articles suggested genetic abnormalities for the 23rd chromosome in their participants).
While we wait for responses from experts to this question, I think that the scenario you mentioned calls for a network meta-analysis. Please check this resource for your consideration: https://training.cochrane.org/handbook/current/chapter-11.
Dear Ray
You can use meta analysis then PCA or FA or CCA. You can use multivariate from genstat or R or m-stat.
You may want to use Regression analysis and check for when treatment is present and when it is not. You will be able to see the effects of the IV in bits by bits based on what you have used to control for the IV.
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