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
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meta4diag.pdf |meta4diag.html
meta4diag/json (API)

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

Peer review:

Datasets:

On CRAN:

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

2.33 score 27 scripts 337 downloads 8 mentions 22 exports 35 dependencies

Last updated 3 years agofrom:9f05944f59. Checks:OK: 6 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winNOTENov 17 2024
R-4.3-macOKNov 17 2024

Exports:AUCAUC.meta4diagcrosshaircrosshair.meta4diagfitted.meta4diagforestforest.meta4diagfunnelfunnel.meta4diagmakeDatamakeObjectmakePriorsmeta4diagmeta4diagGUIplot.meta4diagprint.fitted.meta4diagprint.meta4diagprint.summary.meta4diagrunModelSROCSROC.meta4diagsummary.meta4diag

Dependencies:base64encbitopsbslibcachemcaToolsclicommonmarkcrayondigestfastmapfontawesomefsgluehtmltoolshttpuvjquerylibjsonlitelaterlatticelifecyclemagrittrmemoisemimepromisesR6rappdirsRcpprlangsassshinyshinyBSsourcetoolsspwithrxtable