I'm trying to compare two models using R's nlme package
import rpy2.robjects.robject as r
>> politeness = pd.read_csv('http://www.bodowinter.com/tutorial/politeness_data.csv')
>> mdl1=nlme.gls(Formula('frequency ~ 1'), data=politeness, method="ML", na_action="na.omit")
>> mdl2=nlme.lme(Formula('frequency ~ 1'), data=politeness, method="ML", random=Formula("~1|subject"), na_action="na.omit")
>> print(r.anova(mdl1,mdl2))
This prints lots of output but not the one I'm really interested in. In R I simply get:
Model df AIC BIC logLik Test L.Ratio p-value
mdl1 1 2 932.8611 937.6988 -464.4306
mdl2 2 3 833.2497 840.5063 -413.6249 1 vs 2 101.6114 <.0001
Is there a way to get something similar in python (statsmodels?)?
