I’m interested in running an ordered logit regression in python (using pandas, numpy, sklearn, or something that ecosystem). But I cannot find any way to do this. Is my google-skill lacking? Or is this not something that’s been implemented in a standard package?
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Answer
Update: Logit and Probit Ordinal regression models are now built in to statsmodels.
https://www.statsmodels.org/devel/examples/notebooks/generated/ordinal_regression.html
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from statsmodels.miscmodels.ordinal_model import OrderedModel2
Examples are given in the documentation above. For example:
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import pandas as pd2
from statsmodels.miscmodels.ordinal_model import OrderedModel3
url = "https://stats.idre.ucla.edu/stat/data/ologit.dta"4
data_student = pd.read_stata(url)5
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mod_log = OrderedModel(data_student['apply'],7
data_student[['pared', 'public', 'gpa']],8
distr='logit')9
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res_log = mod_log.fit(method='bfgs', disp=False)11
res_log.summary()12
The catch is that the development version of statsmodels is far ahead of the release. They say that installing the dev version of statsmodels is okay for everyday use. So I used the following:
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pip3 install git+git@github.com:statsmodels/statsmodels.git2
to do so.