R: Fit the Meta-D' Model of Confidence Ratings Using 'brms'

# Fit the Meta-D' Model of Confidence Ratings Using 'brms'

## Documentation for package ‘hmetad’ version 0.1.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

add_epred_draws_metad | Obtain posterior draws of joint response probabilities
add_epred_rvars_metad | Obtain posterior draws of joint response probabilities
add_linpred_draws_metad | Obtain posterior draws of meta-d' model parameters
add_linpred_rvars_metad | Obtain posterior draws of meta-d' model parameters
add_mean_confidence_draws | Obtain posterior draws of mean confidence
add_mean_confidence_rvars | Obtain posterior draws of mean confidence
add_metacognitive_bias_draws | Obtain posterior draws of an index of metacognitive bias
add_metacognitive_bias_rvars | Obtain posterior draws of an index of metacognitive bias
add_predicted_draws_metad | Obtain posterior predictions of joint responses
add_predicted_rvars_metad | Obtain posterior predictions of joint responses
add_roc1_draws | Obtain posterior draws of the pseudo type 1 receiver operating characteristic (ROC) curve.
add_roc1_rvars | Obtain posterior draws of the pseudo type 1 receiver operating characteristic (ROC) curve.
add_roc2_draws | Obtain posterior draws of the response-specific type 2 receiver operating characteristic (ROC) curves.
add_roc2_rvars | Obtain posterior draws of the response-specific type 2 receiver operating characteristic (ROC) curves.
aggregate_metad | Aggregate 'data' by 'response', 'confidence', and other columns
cor_matrix | Generate a correlation matrix with all off-diagonal values equal to 'r'
cov_matrix | Generate a covariance matrix.
epred_draws_metad | Obtain posterior draws of joint response probabilities
epred_rvars_metad | Obtain posterior draws of joint response probabilities
example_data | Simulated data for example model fitting
example_model | Example meta-d' model for model post-processing
fit_metad | Fit the meta-d' model using 'brms' package
joint_response | Convert between separate and joint type 1/type 2 responses
linpred_draws_metad | Obtain posterior draws of meta-d' model parameters
linpred_rvars_metad | Obtain posterior draws of meta-d' model parameters
mean_confidence_draws | Obtain posterior draws of mean confidence
mean_confidence_rvars | Obtain posterior draws of mean confidence
metac2_parameters | Obtain a vector of the names of the 'K-1' parameters representing the differences between successive confidence criteria for the meta-d' model with 'K' levels of confidence.
metacognitive_bias_draws | Obtain posterior draws of an index of metacognitive bias
metacognitive_bias_rvars | Obtain posterior draws of an index of metacognitive bias
metad | 'brms' family for the metad' model
metad_pmf | Generate (log) probability simplex over the joint type 1/type 2 responses
normal_lccdf | Normal cumulative distribution functions
normal_lcdf | Normal cumulative distribution functions
predicted_draws_metad | Obtain posterior predictions of joint responses
predicted_rvars_metad | Obtain posterior predictions of joint responses
response_probabilities | Compute joint response probabilities from aggregated counts
rmatrixnorm | Sample from a matrix-normal distribution
roc1_draws | Obtain posterior draws of the pseudo type 1 receiver operating characteristic (ROC) curve.
roc1_rvars | Obtain posterior draws of the pseudo type 1 receiver operating characteristic (ROC) curve.
roc2_draws | Obtain posterior draws of the response-specific type 2 receiver operating characteristic (ROC) curves.
roc2_rvars | Obtain posterior draws of the response-specific type 2 receiver operating characteristic (ROC) curves.
sim_metad | Simulate from the meta-d' model
sim_metad_condition | Simulate from the meta-d' model across separate conditions
sim_metad_participant | Simulate from the hierarchical meta-d' model
sim_metad_participant_condition | Simulate from the hierarchical meta-d' model across within-participant conditions
stanvars_metad | Generate Stan code for the meta-d' model
to_signed | Convert binary variable x between \{0, 1\} and \{-1, 1\}
to_unsigned | Convert binary variable x between \{0, 1\} and \{-1, 1\}
type1_response | Convert between separate and joint type 1/type 2 responses
type2_response | Convert between separate and joint type 1/type 2 responses