b3lmeta | R Documentation |
This function performers a Bayesian meta-analysis
b3lmeta( data, mean.mu.0 = 0, sd.mu.0 = 10, scale.sigma.between = 0.5, df.scale.between = 1, scale.sigma.within = 0.5, df.scale.within = 1, nr.chains = 2, nr.iterations = 10000, nr.adapt = 1000, nr.burnin = 1000, nr.thin = 1, be.quiet = FALSE, r2jags = TRUE )
data |
A data frame with at least three columns with the following names: 1) TE = treatment effect, 2) seTE = the standard error of the treatment effect. 3) design = indicates study type or clustering subgroup. |
mean.mu.0 |
Prior mean of the overall mean parameter mu.0 (mean across designs), default value is 0. |
sd.mu.0 |
Prior standard deviation of mu.0 (mean across designs), the default value is 10. |
scale.sigma.between |
Prior scale parameter for scale gamma distribution for the precision between study types. The default value is 0.5. |
df.scale.between |
Degrees of freedom of the scale gamma distribution for the precision between study types. The default value is 1, which results in a Half Cauchy distribution for the standard deviation between studies. Larger values e.g. 30 corresponds to a Half Normal distribution. |
scale.sigma.within |
Prior scale parameter for scale gamma distribution for the precision within study types. The default value is 0.5. |
df.scale.within |
Degrees of freedom of the scale gamma distribution for the precision within study types. The default value is 1, which results in a Half Cauchy distribution for the standard deviation between studies. Larger values e.g. 30 corresponds to a Half Normal distribution. |
nr.chains |
Number of chains for the MCMC computations, default 2. |
nr.iterations |
Number of iterations after adapting the MCMC, default is 10000. Some models may need more iterations. |
nr.adapt |
Number of iterations in the adaptation process, default is 1000. Some models may need more iterations during adptation. |
nr.burnin |
Number of iteration discard for burn-in period, default is 1000. Some models may need a longer burnin period. |
nr.thin |
Thinning rate, it must be a positive integer, the default value 1. |
be.quiet |
Do not print warning message if the model does not adapt. The default value is FALSE. If you are not sure about the adaptation period choose be.quiet=TRUE. |
r2jags |
Which interface is used to link R to JAGS (rjags and R2jags), default value is R2Jags=TRUE. |
The results of the object of the class bcmeta can be extracted with R2jags or with rjags. In addition a summary, a print and a plot functions are implemented for this type of object.
This function returns an object of the class "bmeta". This object contains the MCMC output of each parameter and hyper-parameter in the model and the data frame used for fitting the model.
Verde, P.E. (2021) A Bias-Corrected Meta-Analysis Model for Combining Studies of Different Types and Quality. Biometrical Journal; 1–17.
## Not run: library(jarbes) ## End(Not run)
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