BootCI: This functions performs bootstrap to compute the confidence...
In metacart: Meta-CART: A Flexible Approach to Identify Moderators in Meta-Analysis
BootCI R Documentation
This functions performs bootstrap to compute the confidence intervals for the subgroup effect size estimates.
This function is only applicable to Random effects metaregression trees with 2 terminal nodes or more.
Description
This functions performs bootstrap to compute the confidence intervals for the subgroup effect size estimates.
This function is only applicable to Random effects metaregression trees with 2 terminal nodes or more.
Usage
BootCI(Metatree, nboot = 50)
Arguments
Metatree
fitted tree of class REmrt.
nboot
number of bootstrap samples.
Value
tree containing the input tree, the Bootstrap estimates for the effect sizes and standard errors, Bootstrap estimate for tau2, and the Bootstrap bias correction.
Examples
set.seed(12345)
data(dat.BCT2009)
library(Rcpp)
REtree <- REmrt(g ~ T1 + T2+ T4 +T25, vi = vi, data = dat.BCT2009, c.pruning = 0)
BootTree<-BootCI(REtree, nboot = 3)
summary(BootTree)
metacart documentation built on June 8, 2025, 12:46 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| BootCI | R Documentation |
This functions performs bootstrap to compute the confidence intervals for the subgroup effect size estimates. This function is only applicable to Random effects metaregression trees with 2 terminal nodes or more.
Description
This functions performs bootstrap to compute the confidence intervals for the subgroup effect size estimates. This function is only applicable to Random effects metaregression trees with 2 terminal nodes or more.
Usage
BootCI(Metatree, nboot = 50)
Arguments
Metatree |
fitted tree of class |
nboot |
number of bootstrap samples. |
Value
tree containing the input tree, the Bootstrap estimates for the effect sizes and standard errors, Bootstrap estimate for tau2, and the Bootstrap bias correction.
Examples
set.seed(12345)
data(dat.BCT2009)
library(Rcpp)
REtree <- REmrt(g ~ T1 + T2+ T4 +T25, vi = vi, data = dat.BCT2009, c.pruning = 0)
BootTree<-BootCI(REtree, nboot = 3)
summary(BootTree)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.