Please also provide the following information in addition to your question:

- Operating System: Windows 2016 Server
- rstanarm Version: 2.18.2

My mixed effect linear regression model has an outcome variable that is strictly positive.

I am using the weakly informative t_prior.

I have added the family = gaussian(link = ‘log’) to the model arguments.

t_prior <- student_t(df = 7,

location = 0,

scale = 2.5)

StandardizedOME.1e4.stan_glmer <- stan_glmer(

I(StandardizedOME + 1) ~ z.Age + z.AnesthesiaDuration + AnesthesiaTechniqueBlock +

AnesthesiaTechniqueGeneral + AnesthesiaTechniqueNeuraxial + o.ASAClass +

EmergencyStatusYN + Race + Sex + REMI + NonOpioidAnalgesicsCount +

o.AIM1Year + CPTBucket + (1 | MPOGInstitutionID),

data = AIM1Small.1e4.df,

family = gaussian(link = ‘log’),

prior = t_prior,

prior_intercept = t_prior,

chains = 4,

cores = 4

)

Error messages are returned at the start of sampling:

SAMPLING FOR MODEL ‘continuous’ NOW (CHAIN 1).

Chain 1: Rejecting initial value:

Chain 1: Error evaluating the log probability at the initial value.

Chain 1: Exception: normal_lpdf: Location parameter[1] is inf, but must be finite! (in ‘model_continuous’ at line 170)

The model estimation terminates after 100 attempts.

The following text is written to console:

some chains had errors; consider specifying chains = 1 to debughere are whatever error messages were returned

[[1]]

Stan model ‘continuous’ does not contain samples.

[[2]]

Stan model ‘continuous’ does not contain samples.

[[3]]

Stan model ‘continuous’ does not contain samples.

[[4]]

Stan model ‘continuous’ does not contain samples.

Error in check_stanfit(stanfit) :

Invalid stanfit object produced please report bug

Error in dimnamesGets(x, value) :

invalid dimnames given for “dgCMatrix” object

Are there other arguments that must be set to use the log link in the gaussian family?

Nathan