stats.anova.anova_lm()

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

1 2	>>> import statsmodels.api as sm >>> from statsmodels.formula.api import ols

1 2 3 4 5 6 7

>>> 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()

1 2	>>> table = sm.stats.anova_lm(moore_lm, typ=2) # Type 2 ANOVA DataFrame >>> print table