Suppose I am trying to measure people's Happiness depending on Time of Day (Morning/Afternoon/Evening) and Ice Cream Flavor (Chocolate/Strawberry/Vanilla) through a 1-7 scale. Participants are divided into three groups (A/B/C) following the Greco-Latin square design below:
| - | Morning | Afternoon | Evening |
|---|---|---|---|
| Chocolate | A1 | B1 | C1 |
| Strawberry | C2 | A2 | B2 |
| Vanilla | B3 | C3 | A3 |
This way we ensure that, for each participant, we will have a measure for all Times of Day and all Ice Cream Flavors. Suppose we get the data below from 12 participants (column names have the initials for our variables (e.g., m_c = morning_chocolate)):
| id | group | m_c | m_s | m_v | a_c | a_s | a_v | e_c | e_s | e_v |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | B | 4.97 | 2.58 | 2.9 | ||||||
| 2 | A | 1.15 | 2.26 | 6.18 | ||||||
| 3 | A | 6.92 | 1.24 | 4.14 | ||||||
| 4 | C | 4.38 | 5.43 | 6.83 | ||||||
| 5 | B | 2.71 | 3.98 | 5.72 | ||||||
| 6 | C | 2.42 | 5.64 | 6.15 | ||||||
| 7 | A | 5.38 | 3.06 | 6.85 | ||||||
| 8 | B | 5.1 | 1.37 | 6.26 | ||||||
| 9 | C | 6.2 | 6.15 | 5.97 | ||||||
| 10 | B | 6.73 | 1.76 | 6.93 | ||||||
| 11 | A | 5.88 | 3.45 | 5.01 | ||||||
| 12 | C | 2.21 | 5.65 | 5.95 |
Because of the experimental design, each participant will have six empty cells. How can I run a Bayesian Repeated Measures ANOVA analysis in R to measure:
Any effects of Time of Day on Happiness
Any effects of Ice Cream Flavor on Happiness
Any interaction effects between Time of Day and Ice Cream Flavor on Happiness
Posthoc values for all three analyses above
JASP's Bayesian Repeated Measures Analysis gives me the same error reported on this page. I am not proficient in R, so I'm not sure how I can format my data to fit the code provided in the page's last comment and how to implement the posthoc analysis. Any help would be appreciated. Thanks!