# Discrepant results between JASP & BayesFactor - Repeated Measures ANOVA

subj = 1:10,

Hey all

I am finding different results between the two when conducting a bayesian repeated measures anova, and I'm not sure if I'm mis-specifying it (in JASP or BayesFactor) or interpreting the output incorrectly.

Example experiment: Subjects are assigned conditions (treatment vs. control) and take two tests (science and math).

```
df <- data.frame(
subj = 1:10
condition = sample(x=c("treatment", "control"), size = 10, replace = T)
science.score = sample(x = 50:100,size =10, replace = T)
math.score = sample(x = 25:75,size =10, replace = T))
df.long <- melt(df,
variable.name = "test",
value.name = "score",
id.vars = c("subj", "condition"))
```

When I perform a frequentist repeated measures anova in JASP and BayesFactor, the results converge:

However, when I do a Bayesian Repeated Measures ANOVA, the results diverge (or, at least I think they do):

I specified both ANOVAs the same way in JASP, so I'm not sure what I'm doing wrong!

Any help would be much appreciated

## Comments

The difference in the analysis is that JASP compares all models to the Null model

that includes subject.To replicate the results in R you would have to include "subj" into the model as well. In your example, it wasn't included which you can see from the "Against denominator: Intercept only"

A reproducible example:

The results in R:

The results in JASP:

There is still a small numerical discrepancy, but that is nothing to worry about. I hope that solves the issue!

awesome, thank you @vandenman for the help!