This new argument changes how missing data is handled in the model:
If complete_cases = FALSE (default), all missing values are imputed in the model, even when there is no observed data at all for a given taxon. This could be useful for getting posterior predictions for taxa without data. It's also cleaner to explain to users.
If complete_cases = TRUE, we use listwise deletion for cases with any missing data.
This new argument changes how missing data is handled in the model:
complete_cases = FALSE
(default), all missing values are imputed in the model, even when there is no observed data at all for a given taxon. This could be useful for getting posterior predictions for taxa without data. It's also cleaner to explain to users.complete_cases = TRUE
, we use listwise deletion for cases with any missing data.