Returns the names of the parameters/nodes of an object of class 'JointAI' for which a monitor is set.
parameters(object, mess = TRUE, warn = TRUE, ...)
| object | object inheriting from class 'JointAI' |
|---|---|
| mess | logical; should messages be given? Default is
|
| warn | logical; should warnings be given? Default is
|
| ... | currently not used |
# (This function does not need MCMC samples to work, so we will set # n.adapt = 0 and n.iter = 0 to reduce computational time) mod1 <- lm_imp(y ~ C1 + C2 + M2 + O2 + B2, data = wideDF, n.adapt = 0, n.iter = 0, mess = FALSE)#> Warning: #> It is currently not possible to use “contr.poly” for incomplete #> categorical covariates. I will use “contr.treatment” instead. You can #> specify (globally) which types of contrasts are used by changing #> “options('contrasts')”.parameters(mod1)#> #>#> outcome outcat varname coef #> 1 y <NA> (Intercept) beta[1] #> 2 y <NA> C1 beta[2] #> 3 y <NA> C2 beta[3] #> 4 y <NA> M22 beta[4] #> 5 y <NA> M23 beta[5] #> 6 y <NA> M24 beta[6] #> 7 y <NA> O22 beta[7] #> 8 y <NA> O23 beta[8] #> 9 y <NA> O24 beta[9] #> 10 y <NA> B21 beta[10] #> 11 y <NA> <NA> sigma_y