"conditional dependence" in Bayesian analysis

Hey there!

I am working with Bayesian data analysis with BRMS as ‘a real novice’!

I need to resolve an issue where I need something like conditioning the dependent variable.
for example, something like Y|y’ ~ ß1X1 + ß2X2 + ßnXn; where y’ is the condition to the dependent variable, Y, and X1…Xn are the independent variables.

The real data and case I am working with is the adoption of technology by various stakeholders. A vehicle owner or a driver says I would adopt the technology if I am paid $xxx daily to cover any unforeseen uncertainty from adoption. Willingness to adopt is my dependent variable, and the condition is the daily cash demand.

I need your help approaching this in Bayesian analysis with BRMS!


For help with coding in brms, it may help get responses by posting some code you tried, even if it doesn’t work.

I don’t have any code that I have tried. I did one without any conditioning. I have read, but cannot find any leads.

Hey there,
This is what I have tried now and it brings me an error.

fit_VehOwnsWTA_CFC1 ← brm(WTACFCPresState|CashToAcceptCFC~.,

  •                   data = VehOwners_Catvars, family = gaussian(link = "identity"),
  •                   iter = 4000, refresh = 0, chains = 4)

Error: The following addition terms are invalid: