I'd like to hear some people's opinions on what is the most appropriate statistical test to perform on data from drug release studies. Specifically, I've been developing nanoparticles that release their drug contents in response to light, and therefore am looking more at the statistical significance at a specific time point(s) (between nanoparticles exposed to light and those kept in the dark) that an overall difference between release profiles. I've been using T-tests (correcting for multiple comparisons) rather than the usual ANOVA, but wanted to hear some additional feedback.
I think the following link will be helpful to you
http://www.sciencedirect.com/science/article/pii/S1319016411000818.
If the two variables are merely light versus dark conditions across multiple time points, then I'd use a repeated measures ANOVA. This will allow you to check for more complex differences and will allow you to examine the results without using something like a Bonferroni correction. Repeated measures ANOVA are fairly easy to do using most statistical software packages. However, all ANOVA have many assumptions that should be checked.
I recommend any of Todman & Dugard's texts on multivariate analysis. I'm personally familiar with their text "Approaching Multivariate Analysis: An Introduction for Psychology" - which has step by step examples for SPSS along with emphasis on what each important output means, how to interpret, and how to write-up results.
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