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selectMeta
View on CRAN: Click
here
Download and install selectMeta package within the R console
Install from CRAN:
install.packages("selectMeta")
Install from Github:
library("remotes")
install_github("cran/selectMeta")
Install by package version:
library("remotes")
install_version("selectMeta", "1.0.8")
Attach the package and use:
library("selectMeta")
Maintained by
Kaspar Rufibach
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.selectMeta . selectMeta results . selectMeta.pdf . selectMeta_1.0.9.tar.gz . selectMeta_1.0.9.zip . selectMeta_1.0.9.zip . selectMeta_1.0.9.zip . selectMeta_1.0.9.tgz . selectMeta_1.0.9.tgz . selectMeta_1.0.9.tgz . selectMeta_1.0.9.tgz . selectMeta_1.0.9.tgz . selectMeta_1.0.9.tgz . selectMeta archive . https://CRAN.R-project.org/package=selectMeta .
First Published: 2010-11-15
Latest Update: 2015-07-03
Description:
Publication bias, the fact that studies identified for inclusion in a meta analysis do not represent all studies on the topic of interest, is commonly recognized as a threat to the validity of the results of a meta analysis. One way to explicitly model publication bias is via selection models or weighted probability distributions. In this package we provide implementations of several parametric and nonparametric weight functions. The novelty in Rufibach (2011) is the proposal of a non-increasing variant of the nonparametric weight function of Dear & Begg (1992). The new approach potentially offers more insight in the selection process than other methods, but is more flexible than parametric approaches. To maximize the log-likelihood function proposed by Dear & Begg (1992) under a monotonicity constraint we use a differential evolution algorithm proposed by Ardia et al (2010a, b) and implemented in Mullen et al (2009). In addition, we offer a method to compute a confidence interval for the overall effect size theta, adjusted for selection bias as well as a function that computes the simulation-based p-value to assess the null hypothesis of no selection as described in Rufibach (2011, Section 6).
How to cite:
Kaspar Rufibach (2010). selectMeta: Estimation of Weight Functions in Meta Analysis. R package version 1.0.8, https://cran.r-project.org/web/packages/selectMeta. Accessed 10 Apr. 2025.
Previous versions and publish date:
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Complete documentation for selectMeta
Functions, R codes and Examples using
the selectMeta R package
Some associated functions: DearBegg . DearBeggMonotoneCItheta . DearBeggMonotonePvalSelection . IyenGreen . Pval . education . effectBias . pPool . passive_smoking . selectMeta-package . weightLine .
Some associated R codes: Full selectMeta package functions and examples
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