Dichotomising vs keeping categories in regression I'm doing an analysis to see if having children is associated with treatment outcome.
The children variable is categorical and takes values 0-7.
When I dichotomise it into 'children' and 'no children', there is no effect.

But if I keep all the levels, there is a significant association with having 3 children.

I'm not sure how to interpret it. Should I keep all the categories? Is this a real finding or a fluke? I know dichotomising is generally not a good idea but I thought it's warranted with such a variables where Yes and No are so clearcut.
For context, this is not my main research question, I'm looking at many potential risk factors and it's just one of them so I don't necessarily need to analyse it too deeply.

Why not run an ANOVA and see whether adding all the levels improves overall fit? If it does then you can worry about which level is driving it.
