# How to compare several small groups with follow-up data?

I have 4 treatment groups:

1 control (placebo)
1 with X treatment
1 with Y treatment
1 combination-treatment-group XY


and I have monitored the individuals (n=10) in each group by measurement of their tumor volume at baseline, day 1, 3, 7, 10 and 14 to see what treatment is best and how early effect can be seen. What statistics should I use?

The repetitive measurement at day 1, 3, 7, 10 and 14 is some sort of paired comparisons I guess and the comparisons between groups are unpaired. Since there are more than two groups I guess it is ANOVA I should use but will I then have to Bonferroni correct for the fact that I have "looked for the same difference" 5 times?--even though I would expect the difference to show a trend--I would expect the difference between an effective drug and placebo to become greater for each treatment day. I would also like to test if the combination treatment is better than single X and single Y on its own. Since I only have 10 individuals in each group I can not "effort" much Bonferroni correction.

I have done a lot of unpaired and paired t-tests but that might not be correct without any post hoc testing. I am a bit confused about the fact that I lose power because I test more things at once or compare the differences at more than one day. Will it be fair to leave all p-values uncorrected (no Bonferroni) and state that it is a hypothesis generating study testing when a predefined difference can be seen?