Multivariate Random-effects Meta-regression: Updates to Mvmeta

By Ian R. White. 2011

386 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e8224da23284f3943ddcc028dadaefc300804215

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

OpenMEE: Intuitive, open‐source software for meta‐analysis in ecology and evolutionary biology (2017, methodology): “Recently, statistical packages developed for R have emerged as powerful and ﬂexible tools for meta-analysis; for example metafor (Viechtbauer 2010) and mvmeta (White 2011; Gasparrini 2012) are gaining traction in many disciplines.”
Graphical Tools for Network Meta-Analysis in STATA (2013, methodology): “A simple data imputation technique is employed for studies that do not report treatment A that imputes minimal information for the missing reference arm [23,25].”
Visualizing Assumptions and Results in Network Meta-analysis: The Network Graphs Package (2015, methodology): “Using these commands in conjunction with mvmeta (White 2011) or network (White 2015) can simplify the technicalities of the network meta-analysis procedure for dichotomous or continuous data; the commands might be less convenient for other types of data (for example, time-to-event data).”
Network Meta-analysis (2015, methodology): “My mvmeta package performs multivariate meta-analysis and meta-regression (White 2009, 2011, 2015).”
Automating network meta‐analysis (2012, methodology): “The mvmeta package for the Stata statistical software enables MTC in a frequentist framework (White, 2011).”
Multivariate meta-analysis for non-linear and other multi-parameter associations (2012, neutral): “The development of the R package mvmeta has been substantially expedited by the comparison with a previous implementation in Stata provided by Ian White, cited previously.”
Ranking treatments in frequentist network meta-analysis works without resampling methods (2015, neutral): “With this method, a data augmentation step was necessary to impute data for a chosen reference treatment for all studies even if they did not have that treatment arm [25].”
Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies (2012, methodology): “We fitted all models by using mvmeta, a Stata (StataCorp LP. College Station, TX, USA) macro that performs random-effects multivariate meta-regression using restricted maximum likelihood (White, 2011).”
Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression (2012, methodology): “With this reformulation, the model can be fitted by a two-stage procedure using the Stata programme mvmeta (White, 2009, 2011) and the code in Appendix A.1.”