7.7.2.1. 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.

See also

model_results.compare_f_test, model_results.compare_lm_test

Notes

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

Examples

>>> import statsmodels.api as sm
>>> from statsmodels.formula.api import ols

>>> moore = sm.datasets.get_rdataset("Moore", "car",
...                                  cache=True) # load data
>>> 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