Package index • bayesma

Core meta-analysis

Functions for fitting common-effect and random-effects meta-analysis models.

bayesma_mv(): Run a Multivariate Bayesian Meta-Analysis in Stan
bayesma_mv_spec(): Build a bivariate meta-analysis specification object
bayesma_mv_stan_code(): Generate Stan code for a bivariate meta-analysis specification
bayesma_mv_stan_data(): Build the Stan data list for a bivariate meta-analysis specification
bayesma_mv_fit(): Compile and sample a bivariate meta-analysis model
bayesma_mv_extract(): Extract tidy effect components from a bivariate meta-analysis fit
bayesma_mv_output(): Assemble a bayesma_mv object from pipeline outputs

meta_reg(): Bayesian Meta-Regression
coefficient_evidence(): Bayesian Evidence for Meta-Regression Coefficients
metareg_mod_plot(): Plot Method for bayesma_coef_evidence Objects
bubble_plot(): Bubble Plot for Meta-Regression
multi_bubble_plots(): Multi-panel Bubble Plots

robma(): Robust Bayesian Model Averaging for Meta-Analysis
robma_table(): Create a gt Table for RoBMA Results
robma_sensitivity(): Run RoBMA Models Across Multiple Prior Specifications
robma_default_priors(): Default RoBMA prior set
attach_robma_sensitivity(): Attach RoBMA Sensitivity Fits to a bayesma Object
has_robma_sensitivity(): Check if RoBMA Sensitivity Fits are Available

Functions for specifying prior distributions.

normal() half_normal() half_cauchy() half_student_t() exponential() uniform() dirichlet() beta() scaled_inv_chi_sq() lkj(): Prior distribution constructors
prior_bias() prior_weight_function() prior_pet() prior_peese() prior_copas() prior_jung() prior_no_bias(): RoBMA bias-prior constructors

Tools for assessing the trustworthiness of included trials.

inspect_sr(): Run the INSPECT-SR Trustworthiness Assessment
inspect_sr_table(): Per-Check INSPECT-SR Results Table
inspect_plot(): Create INSPECT-SR Trustworthiness Plot
inspect_summary_plot(): Create INSPECT-SR Summary Bar Plot
filter_trustworthy(): Filter Studies by INSPECT-SR Trustworthiness
bayes_carlisle_test(): Bayesian Carlisle's Test for Baseline Balance
bayes_grim_test(): Bayesian GRIM Test
bayes_verify_pvalue(): Bayesian P-Value Verification
carlisle_test(): Carlisle's Test for Baseline Balance
grim_test(): GRIM Test (Granularity-Related Inconsistency of Means)
verify_pvalue(): Verify a Reported P-Value
check_n_consistency(): Check Participant Number Consistency
check_statistics_consistency(): Check Internal Consistency of Summary Statistics
inspect_sr_example: Example INSPECT-SR Dataset: EEG-Guided Anaesthesia and Delirium

Preliminary investigation of meta-analytic data structure.

sensitivity_plot(): Generate Sensitivity Analysis Plot for Bayesian Meta-Analysis
render_sensitivity_patchwork(): Render the stored components into a patchwork object
sens_add_probs() sens_add_null() sens_add_titles() sens_add_x_lim() sens_add_plot_width(): Post-render modifications to a sensitivity plot