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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

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