Estimation of Weight Functions in Meta Analysis
Overview
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).
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 11includes a package overview page
- Examples that run
- 0%2 never run · 5 hold no code
- Exported functions with examples
- 75%
- Documented parameters
- 94%
- Return-value docs
- 88%
- Help pages citing references
- 100%
Downloads
Dependencies
Installing selectMeta adds 1 package (1 with compiled code, 64 KB of source tarballs). Heaviest: DEoptim 64 KB.
Code & Tests
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- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.0.9Latest
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 1.0.82015-07-03 · diff ↗
- RR 3.2.0 released · 2015-04-16
- 1.0.72014-09-06 · diff ↗
- RR 3.1.0 released · 2014-04-10
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- 1.0.62014-02-06 · diff ↗
- 1.0.52013-09-23 · diff ↗
- RR 3.0.0 released · 2013-04-03
- RR 2.15.0 released · 2012-03-30
- 1.0.42011-12-01 · diff ↗ ·
added 20 exports
DearBegg, DearBeggLoglik, DearBeggMonotone, DearBeggMonotoneCItheta, DearBeggMonotonePvalSelection, DearBeggProfileLL, DearBeggToMinimize, DearBeggToMinimizeProfile, dPval, effectBias, Hij, IyenGreenLoglikT, IyenGreenMLE, IyenGreenWeight, normalizeT, pPool, pPval, qPval, rPval, weightLine - RR 2.14.0 released · 2011-10-31
- RR 2.13.0 released · 2011-04-13
- 1.0.32011-03-09 · diff ↗
- 1.0.22011-02-22 · diff ↗
- 1.0.12010-11-26 · diff ↗
- 1.0.02010-11-15
- RR 2.12.0 released · 2010-10-15
Package metadata
- First published
- 2010-11-15
- Total releases
- 10 / 16 yrs
- License
- GPL (>= 2) OSI
- Bundled data
- 0.8 KB / 2 files
- Download size
- 15 KB
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