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_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 |