Package: meta4diag 2.1.1

meta4diag: Meta-Analysis for Diagnostic Test Studies

Bayesian inference analysis for bivariate meta-analysis of diagnostic test studies using integrated nested Laplace approximation with INLA. A purpose built graphic user interface is available. The installation of R package INLA is compulsory for successful usage. The INLA package can be obtained from <https://www.r-inla.org>. We recommend the testing version, which can be downloaded by running: install.packages("INLA", repos=c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/testing"), dep=TRUE).

Authors:Jingyi Guo <[email protected]> and Andrea Riebler <[email protected]>

meta4diag_2.1.1.tar.gz
meta4diag_2.1.1.zip(r-4.7)meta4diag_2.1.1.zip(r-4.6)meta4diag_2.1.1.zip(r-4.5)
meta4diag_2.1.1.tgz(r-4.6-any)meta4diag_2.1.1.tgz(r-4.5-any)
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meta4diag_2.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
meta4diag/json (API)

# Install 'meta4diag' in R:

install.packages('meta4diag', repos = c('https://catefiora.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

Catheter - The Catheter Segment Culture data.
Scheidler - Scheidler dataset.
table_cor - The example table prior for correlation.
table_var - The example table prior for variance.
Telomerase - Telomerase dataset.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.37 score 29 scripts 340 downloads 8 mentions 22 exports 35 dependencies

Last updated from:9f05944f59. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	150
source / vignettes	OK	226
linux-release-x86_64	OK	129
macos-release-arm64	OK	208
macos-oldrel-arm64	OK	149
windows-devel	OK	110
windows-release	OK	136
windows-oldrel	OK	135
wasm-release	OK	132

Exports:AUC AUC.meta4diag crosshair crosshair.meta4diag fitted.meta4diag forest forest.meta4diag funnel funnel.meta4diag makeData makeObject makePriors meta4diag meta4diagGUI plot.meta4diag print.fitted.meta4diag print.meta4diag print.summary.meta4diag runModel SROC SROC.meta4diag summary.meta4diag

Dependencies:base64enc bitops bslib cachem caTools cli commonmark digest fastmap fontawesome fs glue htmltools httpuv jquerylib jsonlite later lattice lifecycle magrittr memoise mime otel promises R6 rappdirs Rcpp rlang sass shiny shinyBS sourcetools sp withr xtable

Help page	Topics
Meta-Analysis for Diagnostic Test Studies	meta4diag-package
A function that calculate the area under summary receiver operating chracteristic line.	AUC AUC.meta4diag
The Catheter Segment Culture data.	Catheter
Crosshair Plot.	crosshair crosshair.meta4diag
Get the estimated values of accuracies for each study.	fitted fitted.meta4diag
Forest plot.	forest forest.grid forest.grid.meta4diag forest.meta4diag
Funnel plot.	funnel funnel.meta4diag
Make internally used data structure.	makeData
A function used to make a 'meta4diag' object.	makeObject
Priors for internal use.	makePriors
Function to analyse diagnostic meta-analysis with Bayesian methods using INLA.	meta4diag
A graphic user interface for meta4diag.	meta4diagGUI
Default meta4diag plotting.	plot.meta4diag
print meta4diag object.	print print.fitted.meta4diag print.meta4diag print.summary.meta4diag
Run the bivariate model.	runModel
Scheidler dataset.	Scheidler
A standard summary receiver operating chracteristic plot.	SROC SROC.meta4diag
Provide summary information.	summary summary.meta4diag
The example table prior for correlation.	table_cor
The example table prior for variance.	table_var
Telomerase dataset.	Telomerase

Package: meta4diag 2.1.1

meta4diag: Meta-Analysis for Diagnostic Test Studies

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)