Conducting Orthogonal Planned Contrasts within Bayesian ANCOVA in JASP/Bayes Factor
I have a 2 (Variable 1: Choice: Choice and No Choice) x3 (Variable 2: Social modelling: Consistent, Inconsistent and control) between subjects design within an ANCOVA containing one categorical covariate(Gender: Male, Female). I have successfully been able to conduct my Bayesian ANCOVA in JASP and R by dummy coding my covariate.
However, now i would like to get bayes factors for each of my orthogonal contrasts (2 main effects of social modelling, 2 interaction effects between social modelling and choice).
I have tried to contrast code my two variables (Choice and Social Modelling) into 4 variables representing each orthogonal contrast and force them in to the analysis as covariates (Along with gender - dummy coded and choice contrast coded). As a proof of concept i did this within a traditional ANOVA in JASP and the contrast coded 4 orthogonal contrasts did give correct P values.
However, when replicate this process within the bayesian ANCOVA, It does not appear to work (checked by contrasting the BF of the Choice variable compared to the null when entered as a fixed factor in my original bayesian ANCOVA and the BF of the choice variable compared to the null when entered as a contrast coded covariate along with all other variables contrast coded)
I would appreciate anyone that could shed light on why the Bayesian analysis differs from the traditional ANCOVA. Specifically why categorical variables are giving different results when contrast/dummy coded and entered as covariates rather than fixed factors. Is this due to a difference in default priors for fixed factors vs covariates?
Alternatively, if anyone could propose an alternative method though which i could get a BF for an orthogonal contrasts (main and interaction) to report alongside my traditional frequentist statistics.