# Robust Bayesian Meta-Analyses

## Documentation for package ‘RoBMA’ version 2.3.2

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

## Help Pages

RoBMA-package | RoBMA: Robust Bayesian meta-analysis
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)
check_RoBMA | Check fitted RoBMA object for errors and warnings
check_setup | Prints summary of '"RoBMA"' ensemble implied by the specified priors
combine_data | Combines different effect sizes into a common metric
d2logOR | Effect size transformations
d2OR | Effect size transformations
d2r | Effect size transformations
d2z | Effect size transformations
diagnostics | Checks a fitted RoBMA object
dwnorm | Weighted normal distribution
effect_sizes | Effect size transformations
forest | Forest plot for a RoBMA object
interpret | Interprets results of a RoBMA model.
is.RoBMA | Reports whether x is a RoBMA object
logOR2d | Effect size transformations
logOR2OR | Effect size transformations
logOR2r | Effect size transformations
logOR2z | Effect size transformations
n_d | Sample sizes to standard errors calculations
n_r | Sample sizes to standard errors calculations
n_z | Sample sizes to standard errors calculations
OR2d | Effect size transformations
OR2logOR | Effect size transformations
OR2r | Effect size transformations
OR2z | Effect size transformations
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.RoBMA | Prints a fitted RoBMA object
print.summary.RoBMA | Prints summary object for RoBMA method
prior | Creates a prior distribution
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
pwnorm | Weighted normal distribution
qwnorm | Weighted normal distribution
r2d | Effect size transformations
r2logOR | Effect size transformations
r2OR | Effect size transformations
r2z | Effect size transformations
RoBMA | Estimate a Robust Bayesian Meta-Analysis
RoBMA.get_option | Options for the RoBMA package
RoBMA.options | Options for the RoBMA package
RoBMA.package | RoBMA: Robust Bayesian meta-analysis
RoBMA_control | Control MCMC fitting process
RoBMA_options | Options for the RoBMA package
RoBMA_package | RoBMA: Robust Bayesian meta-analysis
rwnorm | Weighted normal distribution
sample_sizes | Sample sizes to standard errors calculations
set_autofit_control | Control MCMC fitting process
set_autofit_control, | Control MCMC fitting process
set_convergence_checks | Control MCMC fitting process
se_d | Sample sizes to standard errors calculations
se_d2se_logOR | Standard errors transformations
se_d2se_r | Standard errors transformations
se_d2se_z | Standard errors transformations
se_logOR2se_d | Standard errors transformations
se_logOR2se_r | Standard errors transformations
se_logOR2se_z | Standard errors transformations
se_r | Sample sizes to standard errors calculations
se_r2se_d | Standard errors transformations
se_r2se_logOR | Standard errors transformations
se_r2se_z | Standard errors transformations
se_z | Sample sizes to standard errors calculations
se_z2se_d | Standard errors transformations
se_z2se_logOR | Standard errors transformations
se_z2se_r | Standard errors transformations
standard_errors | Standard errors transformations
summary.RoBMA | Summarize fitted RoBMA object
update.RoBMA | Updates a fitted RoBMA object
weighted_multivariate_normal | Weighted multivariate normal distribution
weighted_normal | Weighted normal distribution
z2d | Effect size transformations
z2logOR | Effect size transformations
z2OR | Effect size transformations
z2r | Effect size transformations
_PACKAGE | RoBMA: Robust Bayesian meta-analysis