lmBF with mixed continuous and categorical IVs
Hi!
Could I just clarify whether mixed categorical and continuous predictors are supported in lmBF? The ?lmBF documentation says
Currently, the function does not allow for general linear models, containing both continuous and categorical predcitors, but this support will be added in the future.
But http://bayesfactorpcl.r-forge.r-project.org/#glm says
Neither function allows the mixing of continuous and categorical covariates. If it is desired to test a model including both kinds of covariates, lmBF function must be used.
Which one is correct?
Many thanks,
Charles
Comments
Hi Charles,
Good question. I'll attend Richard to it.
Cheers,
E.J.
Thanks!
Are you able to provide and update on this? I am running some models right now using lmBF that contain both categorical and continuous predictors.
It works without throwing up an error but I wanted make sure that it is appropriate.
I think you might need to email Richard directly. Keep us posted!
Richard got back to me :)
I will copy and paste in here for anyone who stumbles on this thread.
With regards to whether lmBF allows for the mixing of categorical and continuous predictors:
"Yes, it does. Some of the references are from an older version that didn’t – I might have missed some of the ambiguous references. However, it is very important to realize that for categorical predictors it is important to have them coded as factors, unless you want them treated as numbers (the priors will be different, as detailed in the vignettes)."