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When do you use FDR correction?
The FDR approach is used as an alternative to the Bonferroni correction and controls for a low proportion of false positives, instead of guarding against making any false positive conclusion at all. The result is usually increased statistical power and fewer type I errors.
When is Bonferroni correction not used?
It should not be used routinely and should be considered if: (1) a single test of the ‘universal null hypothesis’ (Ho ) that all tests are not significant is required, (2) it is imperative to avoid a type I error, and (3) a large number of tests are carried out without preplanned hypotheses.
When to use one tailed or two tailed t test?
If there is one group being compared against a standard value (e.g. comparing the acidity of a liquid to a neutral pH of 7), perform a one-sample t-test. One-tailed or two-tailed t-test? If you only care whether the two populations are different from one another, perform a two-tailed t-test.
When to use a paired or two sample t test?
If you are studying one group, use a paired t-test to compare the group mean over time or after an intervention, or use a one-sample t-test to compare the group mean to a standard value. If you are studying two groups, use a two-sample t-test. If you want to know only whether a difference exists, use a two-tailed test.
Can you do more than one t test?
If you accept this assumption (which is standard), then you can do better than performing multiple t tests. Rather than accounting for the standard deviation of just the two groups you are comparing, you can compute it from all the groups.
How to correct for Type 1 error in multiple paired t tests?
As for adjusting, I would likely just do the Bonferroni adjustment. Divide the p value by the number of analyses. In your case, it would likely be .5/4 = .125. If you are doing a one-tailed test (you have an idea of which direction the change should go, which is likely), make sure you are using the one-tailed value.