Function reference • RoBMA

All functions
`Anderson2010`	27 experimental studies from Anderson et al. (2010) that meet the best practice criteria
`Bem2011`	9 experimental studies from Bem (2011) as described in Bem et al. (2011)
`BiBMA()`	Estimate a Bayesian Model-Averaged Meta-Analysis of Binomial Data
`check_RoBMA()`	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()` `check_setup.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 Kroupova et al. (2021)
`Lui2015`	18 studies of a relationship between acculturation mismatch and intergenerational cultural conflict collected by Lui (2015)
`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 Poulsen et al. (2006) 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` `_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
`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
`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

Reference

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