this is an example experiment design for which I would need some help (the values are the same between assays but should be different).
I want to test if the use of drug 1 or drug 2 has a significant effect on the output being measured. The control group was not exposed to any drug. The assay is then repeated 2 more times for statistic significance. Each assay is done at different days with different cells and media.
The problem comes when a statistical test is to be chosen. Here are my thoughts:
- For each assay individually, ANOVA should not be used because I don't want to compare 3 groups, I want to compare the treated groups with the one control group. So, I would do t-test for Control Vs. D1 and Control vs. D2. Is this correct?
But then, there's the 3 assays considered all together and the representation of the data.
Doing a normalization, with Control being 100% and doing the mean of the 3 assays according to the % is a good way to show the data but statistics wise I don't know how to do this. Pooling all measurements for each group and calculate the mean (doing then the t-tests again) doesn't seem appropriate because even the control group usually shows variations. Normalizing, with Control being 100%, seems even wronger, as the Control group(s) won't have any deviation values.
I thought about introducing the Mean-SD-N for each 3 assays but Graphpad doesn't seem to accept that for t-test and 1wayANOVA.