allow_negative_values argument to
fit_metad, which models M-ratio on the identity (rather
than the logarithmic) scale to allow negative values of M-ratiolog_M arguments to simulation functions are renamed to
reflect thistype1_probabilities, type2_probabilities,
joint_probabilities, roc1, roc2,
and mean_confidence), allowing for easy comparison with
model estimatesauroc1, auroc2, auroc1_draws, and
auroc2_draws)by_response argument to roc2_draws
and related functions, allowing for type 2 ROCs collapsed across type 1
responses.stimulus, .response,
.confidence, and .joint_response arguments to
all draws functions, allowing users to specify the names of the
corresponding columnsroc2_drawsposterior_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!