Alteryx Designer Ideas

Share your Designer product ideas - we're listening!

ANOVA tools

We don't have a seperate ANOVA tool in Alteryx, do you think of any reason?


It's not raw data or row blended data but insights gathered that's important:


Linear Regression Tool has a report for Type II ANOVA based on the model table we provide.

But both type II and other types are not available as standalone statistics tools...




Here is the list of different types of Anova that may be useful;


ANOVA models Definitions

t-testsComparison of means between two groups; if independent groups, then independent samples t-test. If not independent, then paired samples t-test. If comparing one group against a fixed value, then a one-sample t-test.
One-way ANOVAComparison of means of three or more independent groups.
One-way repeated measures ANOVAComparison of means of three or more within-subject variables.
Factorial ANOVAComparison of cell means for two or more between-subject IVs.
Comparison of cells means for one or more between-subjects IV and one or more within-subjects IV.
ANCOVAAny ANOVA model with a covariate.
MANOVAAny ANOVA model with multiple DVs. Provides omnibus F and separate Fs.


Looking forward for the addition of ANOVA tools to the data investigation tool box...

Totally in agreement, a repeated measures anova tool would be extremely useful. I'm really surprised we don't have one available considering some of the other more advanced methods in Alteryx. Hopefully this is a low hanging fruit!
Alteryx Partner

Likewise, I was surprised that this wasn't in the predictive toolset. For the ANOVA tool, the only issue that I see is whether or not you allow interaction effects. For example, coding this is pretty easy:

aov(outcome~pr+p2, data=dataset)


A little more difficult if you want to include the interaction and have this become "selectable" in a GUI:

aov(outcome~pr*p2, data=dataset)


But what if you want to code something with a 3-way interaction and include other variables:

aov(outcome~pr*p2*p3 + p4*p5 + p6, data=dataset)


This is the hard part. For Repeated Measures ANOVA, same problem applies for covariates, but added level of complexity given how they pass the time variable (date vs c(1,2,3,4,5)).


Good problem, though. I'll probably take a stab at it over Christmas Break.