posterior_predict() and
posterior_epred() for models with multilevel effects on a
single confidence levelcov_matrix() now works for scalar inputsaggregate_metad() now removes rows with NA
values prior to aggregationmetac2_parameters() function streamlines setting priors
for confidence criteriaaggregate_metad() and fit_metad() now
perform more thorough checks on the number of confidence levels,
Kaggregate_metad() has increased efficiencylinpred_draws_metad/linpred_rvars_metad where
meta_c only used first drawlogit option to use Stan’s
multinomial_logit_lpmf/categorical_logit_lpmfaggregate_metad() now preserves column
types
aggregate_metad() and fit_metad() now
infer K using the maximum confidence level (instead of the
number of unique levels)
aggregate_metad() and fit_metad() now
have more helpful errors/messages for invalid data arguments
Minor updates to package documentation
hmetad is now on CRAN!
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