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)

Poulsen2006

5 studies with a tactile outcome assessment from Poulsen et al. (2006) of the effect of potassium-containing toothpaste on dentine hypersensitivity

RoBMA-package

RoBMA: Robust Bayesian meta-analysis

RoBMA()

Estimate a Robust Bayesian Meta-Analysis

set_autofit_control() set_convergence_checks()

Control MCMC fitting process

RoBMA.options() RoBMA.get_option()

Options for the RoBMA package

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

diagnostics()

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()

Reports whether x is a RoBMA object

plot(<RoBMA>)

Plots a fitted RoBMA object

plot_models()

Models plot for a RoBMA object

print(<RoBMA>)

Prints a fitted RoBMA object

print(<summary.RoBMA>)

Prints summary object for RoBMA method

prior()

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_informed()

Creates an informed prior distribution based on research

prior_none()

Creates a prior distribution

prior_weightfunction()

Creates a prior distribution for a weight function

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(<RoBMA>)

Updates a fitted RoBMA object

dwnorm() pwnorm() qwnorm() rwnorm()

Weighted normal distribution