Hello!
I developed an in-vitro gastrointestinal digestion of a fruit with 3 biological replicates of the colon area. That being said, I want to determine if there is statistical difference through digestion time, considering the 3 colon vessels as replicates. I understand the usual One-way Anova is not an option as I am considering 'time' in this experiment.
Is the repeated measures one-way anova a good option?
How should I proceed after the ANOVA?
Are multiple t-tests with correction (Bonferroni, Holm, Sidak) a better option?
I'd appreciate your help.
This design is a very simple example of a repeated measures or longitudinal design. The difficulty with your question is that you did not specify your variables esp the DV. The first thing to do in this situation is to plot DV against time or it's proxy such as t1,t2,t3 all on the same graph for each experimental unit. What they are is not clear here. These are called spaghetti plots. These plots generally show what's going on. The best ref I know of in longitudinal models (this is a special case) is here:
https://www4.stat.ncsu.edu/~davidian/st732/notes.html
look at the classic repeated measures material in chapt 1 and 2. This should give you the basic repeated measures info to construct your model. then depending
on your software you should be able to deal with the analysis. My favorite multiple comparisons tests are in the attachment to this post. Good luck, David Booth PS a google search like this one should help with your software:
https://www.google.com/search?q=Basic+repeated+measures+tests+in+R&rlz=1C1CHBF_enUS874US874&oq=Basic+repeated+measures+tests+in+R&aqs=chrome..69i57.17339j0j1&sourceid=chrome&ie=UTF-8
Simply replace R with SPSS, SAS, STATA or whatever and follow the examples. Best wishes, D. Booth
If the distribution of your dependent measures are not normal, use the Friedman aligned ranks test, otherwise a regular repeated measures one-way ANOVA. Check the histograms and/or the Shapiro test. If you know R a little, the R script in attachment might be helpful. It includes post hoc tests.
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