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https://github.com/guido-s/metasens

Official Git repository of R package metasens
https://github.com/guido-s/metasens

adjustment cran meta-analysis publication-bias r rstudio

Last synced: about 1 month ago
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Official Git repository of R package metasens

Host: GitHub
URL: https://github.com/guido-s/metasens
Owner: guido-s
License: gpl-2.0
Created: 2015-02-10T16:15:20.000Z (almost 10 years ago)
Default Branch: develop
Last Pushed: 2023-03-31T17:37:42.000Z (almost 2 years ago)
Last Synced: 2024-04-26T03:03:18.017Z (8 months ago)
Topics: adjustment, cran, meta-analysis, publication-bias, r, rstudio
Language: R
Homepage: http://cran.r-project.org/web/packages/metasens/index.html
Size: 653 KB
Stars: 6
Watchers: 2
Forks: 2
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: COPYING

Awesome Lists containing this project

README

        # metasens: Statistical Methods for Sensitivity Analysis in Meta-Analysis

Official Git repository of R package **metasens**

[![License: GPL (>=2)](https://img.shields.io/badge/license-GPL-blue)](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html)

[![CRAN Version](https://www.r-pkg.org/badges/version/metasens)](https://cran.r-project.org/package=metasens)

[![GitHub develop](https://img.shields.io/badge/develop-1.6--0-purple)](https://img.shields.io/badge/develop-1.6--0-purple)

[![Monthly Downloads](https://cranlogs.r-pkg.org/badges/metasens)](https://cranlogs.r-pkg.org/badges/metasens)

[![Total Downloads](https://cranlogs.r-pkg.org/badges/grand-total/metasens)](https://cranlogs.r-pkg.org/badges/grand-total/metasens)

## Description

The following methods are implemented to evaluate how sensitive the results of a meta-analysis are to potential bias in meta-analysis and to support Schwarzer et al. (2015), Chapter 5 "Small-Study Effects in Meta-Analysis":

 - Copas selection model (Copas and Shi, 2001; Schwarzer et al., 2010);

 - limit meta-analysis (Rücker et al., 2011);

 - upper bound for outcome reporting bias (Copas and Jackson, 2004);

 - imputation methods for missing binary data (Gamble & Hollis, 2005; Higgins et al., 2008).

 - LFK index test and Doi plot (Furuya-Kanamori et al., 2018).

Furthermore, R package **metasens** provides functions and datasets to

support Schwarzer et al. (2015), Chapter 5 "Small-Study Effects in

Meta-Analysis", https://link.springer.com/book/10.1007/978-3-319-21416-0 .

### References

[Copas J, Jackson D (2004): A bound for publication bias based on the fraction of unpublished studies. *Biometrics*, **60**, 146-53](https://scholar.google.de/scholar?q=Copas+Jackson+2004+A+bound+for+publication+bias+based+on+the+fraction+of+unpublished+studies)

[Copas JB, Shi JQ (2001): A sensitivity analysis for publication bias in systematic reviews. *Statistical Methods in Medical Research*, **10**, 251-65](https://scholar.google.de/scholar?q=Copas+Shi+2001+A+sensitivity+analysis+for+publication+bias+in+systematic+reviews)

[Furuya-Kanamori L, Barendregt JJ, Doi S (2018): A new improved graphical and quantitative method for detecting bias in meta-analysis. *International Journal of Evidence-Based Healthcare*, **16**, 195-203](https://scholar.google.de/scholar?q=10.1097%2FXEB.0000000000000141)

[Gamble C, Hollis S (2005): Uncertainty method improved on best–worst case analysis in a binary meta-analysis. *Journal of Clinical Epidemiology*, **58**, 579-88](https://scholar.google.de/scholar?q=Gamble+Hollis+2005+Uncertainty+Meta)

[Higgins JPT, White IR, Wood AM (2008): Imputation methods for missing outcome data in meta-analysis of clinical trials. *Clinical Trials*, **5**, 225-39](https://scholar.google.de/scholar?q=Higgins+White+Wood+2008+Imputation+methods+Clinical+Trials)

[Rücker G, Schwarzer G, Carpenter JR, Binder H, Schumacher M (2011): Treatment-effect estimates adjusted for small-study effects via a limit meta-analysis. *Biostatistics*, **12**, 122-42](https://scholar.google.de/scholar?q=Rücker+Schwarzer+Carpenter+Binder+Schumacher+2011+Treatment-effect+estimates+adjusted+for+small-study+effects+via+a+limit+meta-analysis)

[Schwarzer G, Carpenter J, Rücker G (2010): Empirical evaluation suggests Copas selection model preferable to trim-and-fill method for selection bias in meta-analysis. *Journal of Clinical Epidemiology*, **63**, 282-88](https://scholar.google.de/scholar?q=Schwarzer+Carpenter+Rücker+2010+Empirical+evaluation+suggests+Copas+selection+model+preferable+to+trim-and-fill+method+for+selection+bias+in+meta-analysis)

[Schwarzer G, Carpenter JR and Rücker G (2015): *Meta-Analysis with R (Use-R!)*. Springer International Publishing, Switzerland](https://link.springer.com/book/10.1007/978-3-319-21416-0)

## Installation

### Current official [![CRAN Version](https://www.r-pkg.org/badges/version/metasens)](https://cran.r-project.org/package=metasens) release:

```r

install.packages("metasens")

```

### Current [![GitHub develop](https://img.shields.io/badge/develop-1.6--0-purple)](https://img.shields.io/badge/develop-1.6--0-purple) release on GitHub:

Installation using R package

[**remotes**](https://cran.r-project.org/package=remotes):

```r

install.packages("remotes")

remotes::install_github("guido-s/metasens")

```

### Bug Reports:

You can report bugs on GitHub under

[Issues](https://github.com/guido-s/metasens/issues).

or using the R command

```r

bug.report(package = "metasens")

```

(which is not supported in RStudio).