Package: nmathresh 0.1.6.9000

nmathresh: Thresholds and Invariant Intervals for Network Meta-Analysis

Calculation and presentation of decision-invariant bias adjustment thresholds and intervals for Network Meta-Analysis, as described by Phillippo et al. (2018) <doi:10.1111/rssa.12341>. These describe the smallest changes to the data that would result in a change of decision.

Authors:David Phillippo [aut, cre]

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nmathresh/json (API)
NEWS

# Install 'nmathresh' in R:

install.packages('nmathresh', repos = c('https://dmphillippo.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/dmphillippo/nmathresh/issues

Datasets:

SocAnx.post.cov - Posterior covariance matrix from Social Anxiety NMA
SocAnx.post.summary - Posterior summary from Social Anxiety NMA
Thrombo.post.cov - Posterior covariance matrix from Thrombolytics NMA
Thrombo.post.summary - Posterior summary from Thrombolytics NMA

On CRAN:

3.78 score 1 stars 12 scripts 243 downloads 1 mentions 7 exports 21 dependencies

Last updated from:7e2716b977. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	152
source / vignettes	OK	197
linux-release-x86_64	OK	142
macos-release-arm64	OK	103
macos-oldrel-arm64	OK	109
windows-devel	OK	108
windows-release	OK	96
windows-oldrel	OK	104
wasm-release	OK	106

Exports:d_ab2i d_i2ab get.int nma_thresh recon_vcov thresh_2d thresh_forest

Dependencies:cli cpp11 farver ggplot2 glue gridExtra gtable isoband labeling lattice lifecycle Matrix nnls R6 RColorBrewer rlang S7 scales vctrs viridisLite withr

Examples: bias adjustment thresholds for network meta-analysis

David Phillippo, University of Bristol

Rendered fromExamples.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2019-01-07
Started: 2016-12-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Convert contrast indexing	d_ab2i d_i2ab
Get thresholds from U matrix	get.int
Calculate thresholds and invariant intervals	nma_thresh
Reconstruct likelihood covariance matrix	recon_vcov
Posterior covariance matrix from Social Anxiety NMA	SocAnx.post.cov
Posterior summary from Social Anxiety NMA	SocAnx.post.summary
Producing two-dimensional invariant regions	thresh_2d
Producing threshold forest plots	thresh_forest
The thresh class	thresh-class
Posterior covariance matrix from Thrombolytics NMA	Thrombo.post.cov
Posterior summary from Thrombolytics NMA	Thrombo.post.summary