Other packages > Find by keyword >

selectMeta  

Estimation of Weight Functions in Meta Analysis
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", "1.0.9")



Attach the package and use:
library("selectMeta")
Maintained by
Kaspar Rufibach
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2010-11-15
Latest Update: 2025-04-05
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 1.0.9, https://cran.r-project.org/web/packages/selectMeta. Accessed 07 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:02), 1.0.0 (2010-11-15 17:05), 1.0.1 (2010-11-26 17:43), 1.0.2 (2011-02-22 10:00), 1.0.3 (2011-03-09 15:25), 1.0.4 (2011-12-01 09:00), 1.0.5 (2013-09-23 21:55), 1.0.6 (2014-02-06 08:28), 1.0.7 (2014-09-06 20:50), 1.0.8 (2015-07-03 12:51)
Other packages that cited selectMeta R package
View selectMeta citation profile
Other R packages that selectMeta depends, imports, suggests or enhances
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
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

bbricks  
Bayesian Methods and Graphical Model Structures for Statistical Modeling
A set of frequently used Bayesian parametric and nonparametric model structures, as well as a set of ...
Download / Learn more Package Citations See dependency  
modelwordcloud  
Model Word Clouds
Makes a word cloud of text, sized by the frequency of the word, and colored either by user-specified ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
enrichwith  
Methods to Enrich R Objects with Extra Components
Provides the "enrich" method to enrich list-like R objects with new, relevant components. The curren ...
Download / Learn more Package Citations See dependency  
BayesESS  
Determining Effective Sample Size
Determines effective sample size of a parametric prior distribution in Bayesian models. For a web-b ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA