Package: BayesSenMC 0.1.3

BayesSenMC: Different Models of Posterior Distributions of Adjusted Odds Ratio

Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed in <doi:10.1016/j.annepidem.2006.04.001> and <doi:10.1177/0272989X09353452>.

Authors:Jinhui Yang, Haitao Chu, and Lifeng Lin

BayesSenMC_0.1.3.tar.gz
BayesSenMC_0.1.3.zip(r-4.7-x86_64)BayesSenMC_0.1.3.zip(r-4.7-arm64)BayesSenMC_0.1.3.zip(r-4.6-x86_64)BayesSenMC_0.1.3.zip(r-4.6-arm64)BayesSenMC_0.1.3.zip(r-4.5-x86_64)
BayesSenMC_0.1.3.tgz(r-4.6-x86_64)BayesSenMC_0.1.3.tgz(r-4.6-arm64)BayesSenMC_0.1.3.tgz(r-4.5-x86_64)BayesSenMC_0.1.3.tgz(r-4.5-arm64)
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BayesSenMC_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BayesSenMC/json (API)

# Install 'BayesSenMC' in R:

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

Bug tracker:https://github.com/formidify/bayessenmc/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

Datasets:

bd_meta - Meta-analysis data on Bipolar Disorder diagnosis accuracy

On CRAN:

onetbb cpp

2.70 score 412 downloads 9 exports 61 dependencies

Last updated from:dd44806400. Checks:13 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	420
linux-devel-x86_64	NOTE	490
source / vignettes	OK	493
linux-release-arm64	NOTE	387
linux-release-x86_64	NOTE	344
macos-release-arm64	NOTE	499
macos-release-x86_64	NOTE	935
macos-oldrel-arm64	NOTE	561
macos-oldrel-x86_64	NOTE	677
windows-devel-arm64	NOTE	659
windows-devel-x86_64	NOTE	676
windows-release-arm64	NOTE	651
windows-release-x86_64	NOTE	638
windows-oldrel-x86_64	NOTE	553
wasm-release	OK	251

Exports:correctedOR crudeOR diffOR fixedCorrOR logitOR nlmeNDiff paramEst plotOR randCorrOR

Dependencies:abind backports BH boot callr checkmate cli cpp11 desc distributional dplyr farver generics ggplot2 glue gridExtra gtable inline isoband labeling lattice lifecycle lme4 loo magrittr MASS Matrix matrixStats minqa nlme nloptr numDeriv otel pillar pkgbuild pkgconfig posterior processx ps QuickJSR R6 rbibutils RColorBrewer Rcpp RcppEigen RcppParallel Rdpack reformulas rlang rstan rstantools S7 scales StanHeaders tensorA tibble tidyselect utf8 vctrs viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The 'BayesSenMC' package.	BayesSenMC-package BayesSenMC
Meta-analysis data on Bipolar Disorder diagnosis accuracy	bd_meta
Model with constant nondifferential misclassification	correctedOR
Model without misclassification	crudeOR
Model with differential misclassification	diffOR
Model with nondifferential, correlated misclassification	fixedCorrOR
Model with nondifferential, logit normal-distributed misclassification	logitOR
Non-differential Generalized Linear Mixed Effects Model	nlmeNDiff
Parameter estimates of the GLMM model	paramEst
Plot Model	plotOR
Model with nondifferential, randomly correlated misclassification	randCorrOR