low sample size experimental design, t-test vs one way ANOVA I'm designing a biological experiment wherein the sample size is very limited, as each sample is very hard to get. Moreover, I need to have 4 independent groups, each receiving a different treatment.
I only really care about 2 comparisons: group  1 vs group 2, and g3 vs g4. My power analysis indicates my sample size is large enough to compare 1v2 with a t-test and 3v4 with a t-test. However, I worry that doing an ANOVA and post-hocs will lower the statistical power.
Question: If I know beforehand exactly what 2 groups I want to compare (and I don't care about the other comparisons), can I use t-tests instead of ANOVA?
Thanks!

If you reject the null hypothesis in the one-factor ANOVA, then you could do ad hoc comparisons of 1 vs 2 and 3 vs 4 using Tukey's HSD to avoid false discovery on multiple testing of the same data.
(I would not just use two 2-sample t tests.)
Without seeing your data, I can't predict whether those two HSD comparisons would lead to significant results.
HSD uses a somewhat different criterion than ANOVA, so there is no absolute guarantee any HSD comparisons will be significant. Try HSD and see what you find.
