pg.mixed_anova(dv='value', within=['variable_a', 'variable_b'], between = 'group', subject='subject', data=df, effsize="ng2")
returns an dtype error. is this me being an idiot or is it a limitation? i couldnt find a direct mention of it anywhere so thought id check before deep diving
p-val
column)
pingouin
to return the list of outliers found after the robust Shepherd's pi correlation. I checked the source code in master/pingouin/correlation.py
, and the function seems to return an array of booleans, indicating whether they are an outlier or not. However, I suppose this function is wrapped in others, so what I get back in the end is the number of outliers in total. It would be useful to find who are those outliers and inspect them further. Is this possible? Thanks for the good work! :-)
r, p, outliers = shepherd(x, y)
anova
method. I noticed that, once I add a column of categorical values (in str format), the code runs without errors, but I wasn't able to figure out what kind of encoding was applied to the data. Could you help me understanding that?
grp = data.groupby(between, observed=True)
which ensure that categorical levels with no value will be excluded. I would however recommend using string whenever possible!
aov = mixed_anova(dv='rt', between='experiment', within= ['congruent','PC'], subject='subid', data=df)
but I am getting the error: "ValueError: Grouper and axis must be same length". Any ideas? Many thanks!
nan_policy
argument of the pairwise_corr function https://pingouin-stats.org/generated/pingouin.pairwise_corr.html
padjust
parameter to specificy no correction / bonferroni / sidak. For more complex ANOVA designs however, I strongly recommend using JASP instead of Pingouin. Hope this helps!