statsmodels.stats.oneway.anova_generic¶
-
statsmodels.stats.oneway.anova_generic(means, variances, nobs, use_var=
'unequal'
, welch_correction=True
, info=None
)[source]¶ Oneway Anova based on summary statistics
- Parameters:¶
- meansarray_like
Mean of samples to be compared
- variances
float
or array_like Residual (within) variance of each sample or pooled. If
variances
is scalar, then it is interpreted as pooled variance that is the same for all samples,use_var
will be ignored. Otherwise, the variances are used depending on theuse_var
keyword.- nobs
int
or array_like Number of observations for the samples. If nobs is scalar, then it is assumed that all samples have the same number
nobs
of observation, i.e. a balanced sample case. Otherwise, statistics will be weighted corresponding to nobs. Only relative sizes are relevant, any proportional change to nobs does not change the effect size.- use_var{“unequal”, “equal”, “bf”}
If
use_var
is “unequal”, then the variances can differ across samples and the effect size for Welch anova will be computed.- welch_correctionbool
If this is false, then the Welch correction to the test statistic is not included. This allows the computation of an effect size measure that corresponds more closely to Cohen’s f.
- info
not
used
yet
- Returns:¶
- res
results
instance
This includes statistic and pvalue.
- res