Package index • RoBMA

All functions

Anderson2010: 27 experimental studies from anderson2010violent;textualRoBMA that meet the best practice criteria

Andrews2021: 36 estimates of the effect of household chaos on child executive functions with the mean age and assessment type covariates from a meta-analysis by andrews2021examining;textualRoBMA

Bem2011: 9 experimental studies from bem2011feeling;textualRoBMA as described in bem2011must;textualRoBMA

BiBMA(): Estimate a Bayesian Model-Averaged Meta-Analysis of Binomial Data

check_RoBMA() check_RoBMA_convergence(): Check fitted RoBMA object for errors and warnings

check_setup.BiBMA(): Prints summary of "BiBMA.reg" ensemble implied by the specified priors and formula

check_setup() check_setup.RoBMA(): Prints summary of "RoBMA" ensemble implied by the specified priors

check_setup.reg() check_setup.RoBMA.reg(): Prints summary of "RoBMA.reg" ensemble implied by the specified priors and formula

combine_data(): Combines different effect sizes into a common metric

contr.independent(): Independent contrast matrix

contr.meandif(): Mean difference contrast matrix

contr.orthonormal(): Orthornomal contrast matrix

diagnostics() diagnostics_autocorrelation() diagnostics_trace() diagnostics_density(): Checks a fitted RoBMA object

d2r() d2z() d2logOR() d2OR() r2d() r2z() r2logOR() r2OR() z2r() z2d() z2logOR() z2OR() logOR2r() logOR2z() logOR2d() logOR2OR() OR2r() OR2z() OR2logOR() OR2d(): Effect size transformations

forest(): Forest plot for a RoBMA object

interpret(): Interprets results of a RoBMA model.

is.RoBMA() is.RoBMA.reg() is.NoBMA() is.NoBMA.reg() is.BiBMA(): Reports whether x is a RoBMA object

Kroupova2021: 881 estimates from 69 studies of a relationship between employment and educational outcomes collected by kroupova2021student;textualRoBMA

Lui2015: 18 studies of a relationship between acculturation mismatch and intergenerational cultural conflict collected by lui2015intergenerational;textualRoBMA

marginal_plot(): Plots marginal estimates of a fitted RoBMA regression object

marginal_summary(): Summarize marginal estimates of a fitted RoBMA regression object

NoBMA(): Estimate a Bayesian Model-Averaged Meta-Analysis

NoBMA.reg(): Estimate a Bayesian Model-Averaged Meta-Regression

plot(<RoBMA>): Plots a fitted RoBMA object

plot_models(): Models plot for a RoBMA object

Poulsen2006: 5 studies with a tactile outcome assessment from poulsen2006potassium;textualRoBMA of the effect of potassium-containing toothpaste on dentine hypersensitivity

print(<marginal_summary.RoBMA>): Prints marginal_summary object for RoBMA method

print(<RoBMA>): Prints a fitted RoBMA object

print(<summary.RoBMA>): Prints summary object for RoBMA method

prior(): Creates a prior distribution

prior_factor(): Creates a prior distribution for factors

prior_informed(): Creates an informed prior distribution based on research

prior_none(): Creates a prior distribution

prior_PEESE(): Creates a prior distribution for PET or PEESE models

prior_PET(): Creates a prior distribution for PET or PEESE models

prior_weightfunction(): Creates a prior distribution for a weight function

RoBMA-package RoBMA_package RoBMA.package: RoBMA: Robust Bayesian meta-analysis

RoBMA(): Estimate a Robust Bayesian Meta-Analysis

RoBMA.reg(): Estimate a Robust Bayesian Meta-Analysis Meta-Regression

set_autofit_control() set_convergence_checks(): Control MCMC fitting process

RoBMA.options() RoBMA.get_option(): Options for the RoBMA package

se_d() n_d() se_r() n_r() se_z() n_z(): Sample sizes to standard errors calculations

set_default_priors(): Set default prior distributions

se_d2se_logOR() se_d2se_r() se_r2se_d() se_logOR2se_d() se_d2se_z() se_r2se_z() se_r2se_logOR() se_logOR2se_r() se_logOR2se_z() se_z2se_d() se_z2se_r() se_z2se_logOR(): Standard errors transformations

summary(<RoBMA>): Summarize fitted RoBMA object

summary_heterogeneity(): Summarizes heterogeneity of a RoBMA model

update(<BiBMA>): Updates a fitted BiBMA object

update(<RoBMA>): Updates a fitted RoBMA object

weighted_multivariate_normal: Weighted multivariate normal distribution

dwnorm() pwnorm() qwnorm() rwnorm(): Weighted normal distribution