Hey, I need help in figuring out which test/best practice is better for my problem. I've data with 4 different drug group cost and rate of various events (ex: admissions, adverse drug reactions etc.), every outcome is continuous data. I want to say that drug A is cheaper than drug B,C and D, not sure if ANOVA is helpful here as it only say if any group is different from all groups (correct me if I'm wrong). Another problem is I want to refrain from using multiple t-tests (A to B, A to C and A to D) as I feel it's not best practice as you have to do adjustment for 5% error for every t-test comparison and I've to show this in the paper with a new table which would take up space. Appreciate your help. Thanks
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