pingouin.mixed_anova

pingouin.
mixed_anova
(data=None, dv=None, within=None, subject=None, between=None, correction='auto')[source] Mixeddesign (splitplot) ANOVA.
 Parameters
 data
pandas.DataFrame
DataFrame. Note that this function can also directly be used as a Pandas method, in which case this argument is no longer needed.
 dvstring
Name of column containing the dependent variable.
 withinstring
Name of column containing the withinsubject factor (repeated measurements).
 subjectstring
Name of column containing the betweensubject identifier.
 betweenstring
Name of column containing the between factor.
 correctionstring or boolean
If True, return GreenhouseGeisser corrected pvalue. If ‘auto’ (default), compute Mauchly’s test of sphericity to determine whether the pvalues needs to be corrected.
 data
 Returns
 aovDataFrame
ANOVA summary
'Source' : Names of the factor considered 'ddof1' : Degrees of freedom (numerator) 'ddof2' : Degrees of freedom (denominator) 'F' : Fvalues 'punc' : Uncorrected pvalues 'np2' : Partial etasquare effect sizes 'eps' : GreenhouseGeisser epsilon factor ( = index of sphericity) 'pGGcorr' : GreenhouseGeisser corrected pvalues 'Wspher' : Sphericity test statistic 'pspher' : pvalue of the sphericity test 'sphericity' : sphericity of the data (boolean)
See also
Notes
Data are expected to be in longformat (even the repeated measures). If your data is in wideformat, you can use the
pandas.melt()
function to convert from wide to long format.Missing values are automatically removed (listwise deletion) using the
pingouin.remove_rm_na()
function. This could drastically decrease the power of the ANOVA if many missing values are present. In that case, it might be better to use linear mixed effects models.Results have been tested against R and JASP.
Warning
If the betweensubject groups are unbalanced (= unequal sample sizes), a type II ANOVA will be computed. Note however that SPSS, JAMOVI and JASP by default return a type III ANOVA, which may lead to slightly different results.
Examples
For more examples, please refer to the Jupyter notebooks
Compute a twoway mixed model ANOVA.
>>> from pingouin import mixed_anova, read_dataset >>> df = read_dataset('mixed_anova') >>> aov = mixed_anova(dv='Scores', between='Group', ... within='Time', subject='Subject', data=df) >>> aov Source SS DF1 DF2 MS F punc np2 eps 0 Group 5.460 1 58 5.460 5.052 0.028420 0.080  1 Time 7.628 2 116 3.814 4.027 0.020373 0.065 0.999 2 Interaction 5.168 2 116 2.584 2.728 0.069530 0.045 