In Full information maximum likelihood estimation (FIML) of a regression with missing data one jointly estimates
- the regression model parameters and
- the covariance between variables involved in the regression plus some auxiliary variables.
Can this be done in brms?
I want to estimate the effect of E on O.
There is missingness in E, which depends on M. M is also a mediator between E and O.
To obtain an unbiased estimates for the effect of E I would like to estimate jointly the regression model O ~ E, while also imputing the missing data in O and estimating the covariances between O, E, and M.
Thanks in advance, Guido
PS: I can do this directly in Stan, but I am looking for a solution for people who don’t want to write a Stan program.