statsmodels.stats.anova.anova_lm

statsmodels.stats.anova.anova_lm(*args, **kwargs) [source]

Anova table for one or more fitted linear models.

Parameters:

args (fitted linear model results instance) – One or more fitted linear models scale (float) – Estimate of variance, If None, will be estimated from the largest model. Default is None. test (str {"F", "Chisq", "Cp"} or None) – Test statistics to provide. Default is “F”. typ (str or int {"I","II","III"} or {1,2,3}) – The type of Anova test to perform. See notes. robust ({None, "hc0", "hc1", "hc2", "hc3"}) – Use heteroscedasticity-corrected coefficient covariance matrix. If robust covariance is desired, it is recommended to use hc3.

Returns:

anova (DataFrame) A DataFrame containing.

Notes

Model statistics are given in the order of args. Models must have been fit using the formula api.

See also

model_results.compare_f_test, model_results.compare_lm_test

Examples

>>> import statsmodels.api as sm
>>> from statsmodels.formula.api import ols
>>> moore = sm.datasets.get_rdataset("Moore", "car", cache=True) # load
>>> data = moore.data
>>> data = data.rename(columns={"partner.status" :
...                             "partner_status"}) # make name pythonic
>>> moore_lm = ols('conformity ~ C(fcategory, Sum)*C(partner_status, Sum)',
...                 data=data).fit()
>>> table = sm.stats.anova_lm(moore_lm, typ=2) # Type 2 Anova DataFrame
>>> print(table)