Package: MBNMAdose 0.4.3

Hugo Pedder

MBNMAdose: Dose-Response MBNMA Models

Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that incorporate multiple doses within an agent by modelling different dose-response functions, as described by Mawdsley et al. (2016) <doi:10.1002/psp4.12091>. By modelling dose-response relationships this can connect networks of evidence that might otherwise be disconnected, and can improve precision on treatment estimates. Several common dose-response functions are provided; others may be added by the user. Various characteristics and assumptions can be flexibly added to the models, such as shared class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects models and/or by node-splitting at the treatment level.

Authors:Hugo Pedder [aut, cre], Adil Karim [ctb]

MBNMAdose_0.4.3.tar.gz
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MBNMAdose_0.4.3.tgz(r-4.4-any)MBNMAdose_0.4.3.tgz(r-4.3-any)
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MBNMAdose.pdf |MBNMAdose.html
MBNMAdose/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/hugaped/mbnmadose/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • alog_pcfb - Studies of alogliptin for lowering blood glucose concentration in patients with type II diabetes
  • gout - Studies of treatments for Serum Uric Acid reduction in patients with gout
  • osteopain - Studies of treatments for pain relief in patients with osteoarthritis
  • psoriasis100 - Studies of biologics for treatment of moderate-to-severe psoriasis
  • psoriasis75 - Studies of biologics for treatment of moderate-to-severe psoriasis
  • psoriasis90 - Studies of biologics for treatment of moderate-to-severe psoriasis
  • ssi_closure - Studies of wound closure methods to reduce Surgical Site Infections
  • ssri - Studies of Selective Serotonin Reuptake Inhibitors (SSRIs) for major depression
  • triptans - Studies of triptans for headache pain relief

On CRAN:

archivedpackagesr-universe

5.03 score 5 stars 27 scripts 365 downloads 2 mentions 36 exports 42 dependencies

Last updated 6 days agofrom:ba77c94a72 (on package/MBNMAdose). Checks:ERROR: 1 OK: 2 NOTE: 4. Indexed: no.

TargetResultDate
Doc / VignettesFAILNov 20 2024
R-4.5-winOKNov 20 2024
R-4.5-linuxOKNov 20 2024
R-4.4-winNOTENov 20 2024
R-4.4-macNOTENov 20 2024
R-4.3-winNOTENov 20 2024
R-4.3-macNOTENov 20 2024

Exports:%>%calc.edxcumrankdefault.priorsdemaxdevdevdevplotdexpdfpolyditpdloglindmultidnonparamdpolydrop.disconnecteddsplineduserfitplotgensplineget.priorget.relativegetjagsdatainconsistency.loopsmbnma.comparisonsmbnma.networkmbnma.nodesplitmbnma.runmbnma.updatembnma.writenma.nodesplitnma.runnorm2lnormpDcalcrankref.synthrescale.link

Dependencies:abindbackportsbootcheckmateclicodacolorspacecpp11dplyrfansifarvergenericsglueigraphlabelinglatticelifecyclemagrittrMatrixmunsellpillarpkgconfigplyrR2jagsR2WinBUGSR6rbibutilsRColorBrewerRcppRdpackreshape2rjagsrlangscalesstringistringrtibbletidyselectutf8vctrsviridisLitewithr

Class effect NMA analysis using MBNMAdose

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MBNMAdose outputs: Relative effects, forest plots and rankings

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MBNMAdose: Calculating model predictions

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MBNMAdose: Checking for consistency

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MBNMAdose: Exploring the data

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MBNMAdose: Package Overview

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MBNMAdose: Perform a Model-Based Network Meta-Analysis (MBNMA)

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MBNMAdose: Perform Network Meta-Regression

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Readme and manuals

Help Manual

Help pageTopics
Add arm indices and agent identifiers to a datasetadd_index
Studies of alogliptin for lowering blood glucose concentration in patients with type II diabetesalog_pcfb
Calculates values for EDx from an Emax model, the dose at which x% of the maximal response (Emax) is reachedcalc.edx
Update model fit statistics depending on calculation for pDchangepd
Check if all nodes in the network are connected (identical to function in 'MBNMAtime')check.network
Plot cumulative ranking curves from MBNMA modelscumrank
Sets default priors for JAGS model codedefault.priors
Emax dose-response functiondemax
Dev-dev plot for comparing deviance contributions from two modelsdevdev
Plot deviance contributions from an MBNMA modeldevplot
Exponential dose-response functiondexp
Fractional polynomial dose-response functiondfpoly
Integrated Two-Component Prediction (ITP) functionditp
Log-linear (exponential) dose-response functiondloglin
Agent-specific dose-response functiondmulti
Non-parameteric dose-response functionsdnonparam
Polynomial dose-response functiondpoly
Adds placebo comparisons for dose-response relationshipDR.comparisons
Drop treatments from multi-arm (>2) studies for node-splittingdrop.comp
Drop studies that are not connected to the network reference treatmentdrop.disconnected
Spline dose-response functionsdspline
User-defined dose-response functionduser
Plot fitted values from MBNMA modelfitplot
Automatically generate parameters to save for a dose-response MBNMA modelgen.parameters.to.save
Generates spline basis matrices for fitting to dose-response functiongenspline
Get current priors from JAGS model codeget.prior
Calculates league table of effects between treatments in MBNMA and/or NMA modelsget.relative
Prepares data for JAGSgetjagsdata
Studies of treatments for Serum Uric Acid reduction in patients with goutgout
Identify comparisons in loops that fulfill criteria for node-splittinginconsistency.loops
Identify unique comparisons within a networkmbnma.comparisons
Node-splitting model for testing consistency at the treatment level using MBNMAmbnma.nodesplit plot.nodesplit
Run MBNMA dose-response modelsmbnma.run
Update MBNMA to monitor deviance nodes in the modelmbnma.update
Validates that a dataset fulfills requirements for MBNMAmbnma.validate.data
Write MBNMA dose-response model JAGS codembnma.write
Node-splitting model for testing consistency at the treatment-levelnma.nodesplit plot.nma.nodesplit
Convert normal distribution parameters to corresponding log-normal distribution parametersnorm2lnorm
Studies of treatments for pain relief in patients with osteoarthritisosteopain
Calculate plugin pD from a JAGS model with univariate likelihood for studies with repeated measurementspDcalc
Forest plot for results from dose-response MBNMA modelsplot.mbnma
Create an mbnma.network objectmbnma.network plot.mbnma.network
Plots predicted responses from a dose-response MBNMA modelplot.mbnma.predict
Plot histograms of rankings from MBNMA modelsplot.mbnma.rank
Run an NMA modelnma.run plot.nma
Predict responses for different doses of agents in a given population based on MBNMA dose-response modelspredict.mbnma
Print mbnma.network information to the consoleprint.mbnma.network
Print summary information from an mbnma.predict objectprint.mbnma.predict
Prints summary information about an mbnma.rank objectprint.mbnma.rank
Prints summary results from an nma.nodesplit objectprint.nma.nodesplit
Prints summary results from a nodesplit objectprint.nodesplit
Print posterior medians (95% credible intervals) for table of relative effects/mean differences between treatments/classesprint.relative.array
Studies of biologics for treatment of moderate-to-severe psoriasis (100% improvement)psoriasis100
Studies of biologics for treatment of moderate-to-severe psoriasis (>=75% improvement)psoriasis75
Studies of biologics for treatment of moderate-to-severe psoriasis (>=90% improvement)psoriasis90
Set rank as a methodrank
Rank parameter estimatesrank.mbnma
Rank predicted doses of different agentsrank.mbnma.predict
Rank relative effects obtained between specific dosesrank.relative.array
Assigns agent or class variables numeric identifiersrecode.agent
Synthesise single arm dose = 0 / placebo studies to estimate E0ref.synth
Rescale data depending on the link function providedrescale.link
Studies of wound closure methods to reduce Surgical Site Infections (SSI)ssi_closure
Studies of Selective Serotonin Reuptake Inhibitors (SSRIs) for major depressionssri
Print summary of MBNMA results to the consolesummary.mbnma
Print summary mbnma.network information to the consolesummary.mbnma.network
Produces a summary data frame from an mbnma.predict objectsummary.mbnma.predict
Generates summary data frames for an mbnma.rank objectsummary.mbnma.rank
Generates a summary data frame for nma.nodesplit objectssummary.nma.nodesplit
Generates a summary data frame for nodesplit objectssummary.nodesplit
Studies of triptans for headache pain relieftriptans