**0**wrote:

Hello all,

I have a question regarding multiple testing. I have been looking everywhere but I haven't found a suitable answer yet.

So, the situation is like this, I have two different situations.

A) The first situation I have a GLMM that has the following structure.

Response1 ~ Variable1 + Confounder1 + Confounder2 + (1|Random Effect)

In this case, I have data from 1000 individuals, and I am interested in the relationship (and p-value) between Response1 and Variable1. Both response1 and variable1 are numeric variables. My question is, do I have to correct this p-value for the number of iterations in the model (1000 because of the number of individuals)? Do I have to correct it at all?

B) The second situation is very similar to the first one. This time, I have 50 Responses and 4 Variables. What I do now, is fixing the Variable, I run a different GLMM for each one of the 50 responses.

Response1 ~ Variable1 + Confounder1 + Confounder2 + (1|Random Effect)

Response2 ~ Variable1 + Confounder1 + Confounder2 + (1|Random Effect)

Response3 ~ Variable1 + Confounder1 + Confounder2 + (1|Random Effect)

...

Response50 ~ Variable1 + Confounder1 + Confounder2 + (1|Random Effect)

In this case, for the same Variable (Variable1), I would have 50 different p-values from the 50 different models. In this case, I would correct by the number of tests (50), but the question in A remains. Do I also have to consider the intra model number tests?

**66k**• written 2.9 years ago by MHMMH •

**0**