bayes factor hypothesis test in ANCOVA as a alternative for linear mixed model
I want to test whether or not two groups of people have differences in one continuous outcome. But those data are collapsed from 3 different datasets, and I also have 2 categorical variables and 2 continuous variables that need to "control".
I first tried linear mixed model, one continuous outcome as DV, group and 4 covariates as fixed factor, and dataset label as a random factor(both for intercept and group slope). I find a nonsignificant p value.
Then I want to try the Bayes factor hypothesis test for the evidence of the null hypothesis. I noticed there has no Bayes factor test implemented in "Bayesian linear mixed model" in JASP and some posts recommend the "ANCOVA" module. So I was wondering:
(1) Could I do Bayesian ANCOVA to test the group difference? If I'm in the right way, should I enter the categorical covariate in fixed factors and continuous covariate in covariate box (this box has a label indicating only continuous measure....) then adding all of them to null model ? Alternatively, I can enter all covariates in covariate box...
(2) Some classmates also suggest me to decomposite the random factor(dataset label) into several dummy variables (ie, dataset1 = 1, others = 0; dateset2 = 1, others = 0; and so on) then treat them as covariates in Baysian ANCOVA analysis. Did this sound more reasonable?
Any help is welcome, thanks a lot for reading!