I'm coming from SPSS where I was taught that each line is an individual person's score.
Right now, however, I have long-form data, where each person's attitude was measured before and after seeing a photo, 24 times.
| participant | attitude 1 | attitude 2 | gender | height |
|---|---|---|---|---|
| 1 | 2.5 | 4.5 | 0 | 1 |
| 1 | 5.3 | 6.2 | 0 | 1 |
| 1 | 3.3 | 2.4 | 0 | 1 |
| 1 | 6.5 | 7.6 | 0 | 1 |
Everytime I watch a walk through on python to do a repeated measures anova, they always only have one dependent variable. But, in a repeated measures, I have 2. Do I need to use groupby somehow?
This is the code I'm using:
import pingouin as pg
# Compute the two-way mixed-design ANOVA
a = pg.mixed_anova(dv='??', within=['gender','height'],
subject='participant', data=df)
