R: Dose-Response MBNMA Models

# Dose-Response MBNMA Models

## Documentation for package ‘MBNMAdose’ version 0.5.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

add_index | Add arm indices and agent identifiers to a dataset
alog_pcfb | Studies of alogliptin for lowering blood glucose concentration in patients with type II diabetes
calc.edx | Calculates values for EDx from an Emax model, the dose at which x% of the maximal response (Emax) is reached
check.network | Check if all nodes in the network are connected (identical to function in 'MBNMAtime')
cumrank | Plot cumulative ranking curves from MBNMA models
default.priors | Sets default priors for JAGS model code
demax | Emax dose-response function
devdev | Dev-dev plot for comparing deviance contributions from two models
devplot | Plot deviance contributions from an MBNMA model
dexp | Exponential dose-response function
dfpoly | Fractional polynomial dose-response function
ditp | Integrated Two-Component Prediction (ITP) function
dloglin | Log-linear (exponential) dose-response function
dmulti | Agent-specific dose-response function
dnonparam | Non-parameteric dose-response functions
dpoly | Polynomial dose-response function
DR.comparisons | Adds placebo comparisons for dose-response relationship
drop.comp | Drop treatments from multi-arm (>2) studies for node-splitting
drop.disconnected | Drop studies that are not connected to the network reference treatment
dspline | Spline dose-response functions
duser | User-defined dose-response function
fitplot | Plot fitted values from MBNMA model
gen.parameters.to.save | Automatically generate parameters to save for a dose-response MBNMA model
genspline | Generates spline basis matrices for fitting to dose-response function
get.prior | Get current priors from JAGS model code
get.relative | Calculates league table of effects between treatments in MBNMA and/or NMA models
getjagsdata | Prepares data for JAGS
gout | Studies of treatments for Serum Uric Acid reduction in patients with gout
inconsistency.loops | Identify comparisons in loops that fulfill criteria for node-splitting
mbnma.comparisons | Identify unique comparisons within a network
mbnma.network | Create an mbnma.network object
mbnma.nodesplit | Node-splitting model for testing consistency at the treatment level using MBNMA
mbnma.run | Run MBNMA dose-response models
mbnma.update | Update MBNMA to monitor deviance nodes in the model
mbnma.validate.data | Validates that a dataset fulfills requirements for MBNMA
mbnma.write | Write MBNMA dose-response model JAGS code
nma.nodesplit | Node-splitting model for testing consistency at the treatment-level
nma.run | Run an NMA model
norm2lnorm | Convert normal distribution parameters to corresponding log-normal distribution parameters
osteopain | Studies of treatments for pain relief in patients with osteoarthritis
pDcalc | Calculate plugin pD from a JAGS model with univariate likelihood for studies with repeated measurements
plot.mbnma | Forest plot for results from dose-response MBNMA models
plot.mbnma.network | Create an mbnma.network object
plot.mbnma.predict | Plots predicted responses from a dose-response MBNMA model
plot.mbnma.rank | Plot histograms of rankings from MBNMA models
plot.nma | Run an NMA model
plot.nma.nodesplit | Node-splitting model for testing consistency at the treatment-level
plot.nodesplit | Node-splitting model for testing consistency at the treatment level using MBNMA
predict.mbnma | Predict responses for different doses of agents in a given population based on MBNMA dose-response models
print.mbnma.network | Print mbnma.network information to the console
print.mbnma.predict | Print summary information from an mbnma.predict object
print.mbnma.rank | Prints summary information about an mbnma.rank object
print.nma.nodesplit | Prints summary results from an nma.nodesplit object
print.nodesplit | Prints summary results from a nodesplit object
print.relative.array | Print posterior medians (95% credible intervals) for table of relative effects/mean differences between treatments/classes
psoriasis100 | Studies of biologics for treatment of moderate-to-severe psoriasis (100% improvement)
psoriasis75 | Studies of biologics for treatment of moderate-to-severe psoriasis (>=75% improvement)
psoriasis90 | Studies of biologics for treatment of moderate-to-severe psoriasis (>=90% improvement)
rank | Set rank as a method
rank.mbnma | Rank parameter estimates
rank.mbnma.predict | Rank predicted doses of different agents
rank.relative.array | Rank relative effects obtained between specific doses
recode.agent | Assigns agent or class variables numeric identifiers
ref.synth | Synthesise single arm dose = 0 / placebo studies to estimate E0
rescale.link | Rescale data depending on the link function provided
ssi_closure | Studies of wound closure methods to reduce Surgical Site Infections (SSI)
ssri | Studies of Selective Serotonin Reuptake Inhibitors (SSRIs) for major depression
summary.mbnma | Print summary of MBNMA results to the console
summary.mbnma.network | Print summary mbnma.network information to the console
summary.mbnma.predict | Produces a summary data frame from an mbnma.predict object
summary.mbnma.rank | Generates summary data frames for an mbnma.rank object
summary.nma.nodesplit | Generates a summary data frame for nma.nodesplit objects
summary.nodesplit | Generates a summary data frame for nodesplit objects
triptans | Studies of triptans for headache pain relief