Specifying which category to treat as the base with 'statsmodels'

Question

In understand that when I have a category variable in a model passed to a statsmodels fit that dummy variables will automatically be generated for the categories. For example if I have a variable 'Location' with values 'IndianOcean', 'Thailand', 'China' and 'Mars' I will get variables in my model of the form

Location[T.Thailand]

with one of the value not represented. By default the excluded variable seems to be the least common one. Is there a way to specify — ideally within the model specification — which value is treated as the "base value" and excluded?

Answer 1

You can pass a reference arg to the Treatment contrast, using syntax like

"y ~ C(Location, Treatment(reference='China'))"

http://patsy.readthedocs.org/en/latest/API-reference.html#patsy.Treatment

If you have a better suggestion for naming conventions please file an issue with patsy.

Answer 2

If you use single quotes to wrap your string, reference's argument needs to be wrapped with double quotes. Very easy mistake to make. I was using single quotes on both.

For example:

'y ~ C(Location, Treatment(reference="China"))'

is correct.

'y ~ C(Location, Treatment(reference='China'))'

is not correct.

Answer 3

Ok, maybe someone will find this one helpfull. I needed to set a new baseline category for the dependent variable, I had no idea how to do it. I searched and found nothing, so i simply added a "_" for the other categories. If you have 3 categories A, B, C, and you want your baseline to be C you just change the labeles from A and B to _A and _B. It works. I appears that the baseline category is defined by sorted()

Maybe someone knows a proper way to do it, this is not very phytonic, ja.