Function to create posterior distribution plots for summary estimates and between-study standard deviation based on output from bmeta
● Data Source:
CranContrib
● Keywords: Bayesian meta-analysis
● Alias: posterior.plot
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The writeModel function helps to select the proper model to be contained in the 'model.file' for MCMC simulation based on users' specifications.
● Data Source:
CranContrib
● Keywords:
● Alias: writeModel
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Function to produce plot based on different diagnostic statistics
● Data Source:
CranContrib
● Keywords: Diagnostics, MCMC
● Alias: diag.plot
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Function to create autocorrelation function plot to assess convergence
● Data Source:
CranContrib
● Keywords: Autocorrelation, MCMC
● Alias: acf.plot
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The bmeta package provides a collection of functions for conducting meta-analyses under Bayesian context in R. The package includes functions for computing various effect size or outcome measures (e.g. odds ratios, mean difference and incidence rate ratio) for different types of data based on MCMC simulations. Users are allowed to fit fixed- and random-effects models with different priors to the data. Meta-regression can be carried out if effects of additional covariates are observed. Furthermore, the package provides functions for creating posterior distribution plots and forest plot to display main model output. Traceplots and some other diagnostic plots are also available for assessing model fit and performance.
● Data Source:
CranContrib
● Keywords: Bayesian meta-analysis
● Alias: bmeta-package
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Function to examine publication bias. For both fixed- and random-effects models, estimates from no-pooling effects model are used as study-specific estimates. For random-effects models, the corresponding fixed-effects models are implemented at background to obtain pooled estimate. For example, if users call bmeta to run random-effects meta-analysis with normal prior, fixed-effects meta-analysis with normal prior are implemented at background to obtain pooled estimate for graphing. In the absence of publication and heterogeneity, the scatter resembles a symmetrical funnel and the triangle area formed by connecting the centred summary estimate with its 2.5% and 97.5% quantiles on either side includes about 95% of the studies if the fixed-effects model assumption holds (i.e. all the studies estimate the same effect).
● Data Source:
CranContrib
● Keywords: Funnel plot
● Alias: funnel.plot
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Function to print output from function bmeta
● Data Source:
CranContrib
● Keywords:
● Alias: print.bmeta
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A function to call package forestplot from R library and produce forest plot using results from bmeta. The posterior estimate and credible interval for each study are given by a square and a horizontal line, respectively. The summary estimate is drawn as a diamond.
● Data Source:
CranContrib
● Keywords: Forest plot
● Alias: forest.plot
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Function to display a plot of iteration vs. sample values for each variable in the chain
● Data Source:
CranContrib
● Keywords: Diagnostics, MCMC
● Alias: traceplot.bmeta
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Function to fit the Bayesian fixed- and random-effects meta-analytic models with or without moderators. Models are designed to include non-informative priors.
● Data Source:
CranContrib
● Keywords: Bayesian meta-analysis
● Alias: bmeta, bmeta.default
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