R package metasens provides advanced statistical methods to model and adjust bias in meta-analysis and supports Schwarzer et al. (2015), Chapter 5 "Small-Study Effects in Meta-Analysis" https://link.springer.com/book/10.1007/978-3-319-21416-0.
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
R package metasens is an add-on package for meta providing the following meta-analysis methods:
Copas selection model (function copas)
described in Copas & Shi (2001) and evaluated in Schwarzer et
al., 2010);
limit meta-analysis (limitmeta) by Rücker et
al. (2011);
upper bound for outcome reporting bias
(orbbound) described in Copas & Jackson (2004);
imputation methods for missing binary data
(metamiss) described in Gamble & Hollis (2005) and
Higgins et al. (2008).
Furthermore, functions and datasets from metasens are utilised in Schwarzer et al. (2015), Chapter 5 "Small-Study Effects in Meta-Analysis", https://link.springer.com/book/10.1007/978-3-319-21416-0.
Type help(package = "metasens") for a listing of R functions
available in metasens.
Type citation("metasens") on how to cite metasens in
publications.
To report problems and bugs
type bug.report(package = "metasens") if you do not
use RStudio,
send an email to Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de if you use RStudio.
The development version of metasens is available on GitHub https://github.com/guido-s/metasens.
Copas J, Jackson D (2004): A bound for publication bias based on the fraction of unpublished studies. Biometrics, 60, 146--53
Copas JB, Shi JQ (2001): A sensitivity analysis for publication bias in systematic reviews. Statistical Methods in Medical Research, 10, 251--65
Furuya-Kanamori L, Barendregt JJ, Doi SAR (2018): A new improved graphical and quantitative method for detecting bias in meta-analysis. International Journal of Evidence-Based Healthcare, 16, 195--203
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
Higgins JPT, White IR, Wood AM (2008): Imputation methods for missing outcome data in meta-analysis of clinical trials. Clinical Trials, 5, 225--39
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
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--8
Schwarzer G, Carpenter JR, Rücker G (2015): Meta-Analysis with R (Use-R!). Springer International Publishing, Switzerland
Schwarzer G, Rücker G, Semaca C (2024): LFK index does not reliably detect small-study effects in meta-analysis: a simulation study. Research Synthesis Methods, Accepted for publication