2 Way ANOVA or multiple t tests with correction?

Hi all,

I am trying to do some data analysis, and I'm not sure whether to use a 2 way ANOVA or multiple t tests with Bonferroni correction.

I am looking at the effect of a chemical on bacterial binding to different polymers. So for each polymer, I want to know if there is a difference in binding between the treatment group and the control group.

I initially wanted to do a 2 way ANOVA with multiple comparisons because I have two independent variables (polymer and treatment group) and one dependent variable (bacterial binding). However, would multiple t tests with correction be more appropriate if I am only comparing each polymer +/- treatment, and not comparing the polymers to each other?

I really hope a 2 way ANOVA with multiple comparisons is ok for this data, because I have spent a LONG time making all my figures using the ANOVA data.... :D

Thanks in advance for you input!!!
Last edited:


No cake for spunky
Why would you not compare the impact of the polymer on the DV? I can't see any advantage if that is an IV.

In general ANOVA is recommended to multiple t test, although I have not seen anyone do what you are.
Thanks for your response!

I do want to look at the impact of the polymer, but I only want to compare each polymer to itself +/- treatment, not to the other polymers. So the experimental design is "for each polymer, is there a difference in binding +/- treatment?" I am not looking to see if the binding differs between polymers.


No cake for spunky
It seems then that you are in practice running one predictor (treatment)within each "group" (the specific polymer). That is one regression for each polymer. In that case ANOVA and single t test should generate identical results - its your choice which you use.