# Bonferonni versus FDR

My question is rather simple: When should you use the Bonferroni correction over the FDR correction?

I've read about that the Bonferroni correction applies a more conservative approach in comparison with the FDR correction. Additional, the FDR should be more accurate with more pvalues (how much is more?).

I applied both p adjustment methods and can clearly see that the Bonferroni is more conservative (table and figure). But how would I know which method to use?

In my case I have 20 pvalues derived from 20 separate glm's (binomial):

     Original    FDR           Bonferroni
X1   0.00516     0.0121      0.1033
X2   0.00000     0.0000      0.0000
X3   0.00128     0.0051      0.0255
X4   0.01730     0.0316      0.3461
X5   0.00545     0.0121      0.1091
X6   0.75503     0.7550      1.0000
X7   0.54320     0.6036      1.0000
X8   0.31668     0.4222      1.0000
X9   0.68161     0.7175      1.0000
X10  0.01737     0.0316      0.3474
X11  0.02543     0.0391      0.5086
X12  0.02055     0.0343      0.4110
X13  0.04737    0.06767      0.9474
X14  0.00063     0.0042      0.0126
X15  0.00109     0.0051      0.0217
X16  0.37707     0.4713      1.0000
X17  0.00046     0.0042      0.0092
X18  0.00191     0.0064      0.0381
X19  0.00402     0.0115      0.0805
X20  0.47011     0.5531      1.0000


As you can see the Bonferroni is as expected conservative as it leaves most of the pvalues above 0.05. When looking at the correlations between the significant X variables and the response variable (for both adjustment methods) an ecological meaningful explanation can be formulated. However, just looking at the pvalues is there a way to say which method is more appropriate?