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Added `feature-selection` tag. This seems more relevant than the other tags already included.
Nick Cox
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Appropriately selecting explanatory (independent) variables

My aim is to carry out a GLM.

I have 400 sites where I have count data of animals (response variable) and environmental characteristics (explanatory variables). At the moment I have around 40 explanatory variables.

The examples I have seen so far only have up to 10 explanatory variables so I guess I have to choose among the explanatory variables. How many explanatory variables normally are selected?

I read that no more than 10% of the number of responses should be chosen as the number of explanatory variables (which in my case is 40). Is that a general rule?

Are there any statistical tests which I can use to select the most appropriate explanatory variables? So far knowledge about the relationship of the explanatory variables and the animals is low and I can therefore not select my explanatory variables based on theory.

Moreover: How can I deal with multicollinearity and interactions of 40 explanatory variables?

kalakaru
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