# Run Time-Course MBNMA Models

## Documentation for package ‘MBNMAtime’ version 0.1.3

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

## Help Pages

add_index | Add follow-up time and arm indices to a dataset
alog_pcfb | Studies of alogliptin for lowering blood glucose concentration in patients with type II diabetes
compound.beta | Prepares beta time-course parameters for mb.write()
devplot | Plot deviance contributions from an MBNMA model
fitplot | Plot fitted values from MBNMA model
gen.parameters.to.save | Automatically generate parameters to save for a dose-response MBNMA model
genmaxcols | Get large vector of distinct colours using Rcolorbrewer
get.earliest.time | Create a dataset with the earliest time point only
get.latest.time | Create a dataset with the latest time point only
get.model.vals | Get MBNMA model values
get.prior | Get current priors from JAGS model code
getjagsdata | Prepares data for JAGS
goutSUA_CFB | Studies of treatments for reducing serum uric acid in patients with gout
goutSUA_CFBcomb | Studies of combined treatments for reducing serum uric acid in patients with gout
inconsistency.loops | Identify comparisons in loops that fulfill criteria for node-splitting
mb.comparisons | Identify unique comparisons within a network (identical to MBNMAdose)
mb.emax | Run MBNMA model with an Emax time-course function (without a Hill parameter)
mb.emax.hill | Run MBNMA model with an Emax time-course function and a Hill parameter
mb.exponential | Run MBNMA model with an exponential time-course function
mb.fract.first | Run MBNMA model with a first-order fractional polynomial time-course function
mb.fract.second | Run MBNMA model with a second-order fractional polynomial time-course function
mb.linear | Run MBNMA model with a linear time-course function
mb.make.contrast | Convert arm-based MBNMA data to contrast data
mb.network | Create an mb.network object
mb.nodesplit | Perform node-splitting on a MBNMA time-course network
mb.nodesplit.comparisons | Identify comparisons in time-course MBNMA datasets that fulfill criteria for node-splitting
mb.piecelinear | Run MBNMA model with a piecewise linear time-course function
mb.quadratic | Run MBNMA model with a quadratic time-course function
mb.run | Run MBNMA time-course models
mb.update | Update MBNMA to obtain deviance contributions or fitted values
mb.validate.data | Validates that a dataset fulfills requirements for MBNMA
mb.write | Write MBNMA time-course models JAGS code
obesityBW_CFB | Studies of treatments for reducing body weight in patients with obesity
osteopain | Studies of pain relief medications for osteoarthritis
pDcalc | Calculate plugin pD from a JAGS model with univariate likelihood for studies with repeated measurements
plot.mb.network | Create an mb.network object
plot.mb.nodesplit | Perform node-splitting on a MBNMA time-course network
plot.mb.predict | Plots predicted responses from a time-course MBNMA model
plot.mb.rank | Plot histograms of rankings from MBNMA models
plot.mbnma | Forest plot for results from time-course MBNMA models
predict.mbnma | Predict responses over time in a given population based on MBNMA time-course models
print.mb.network | Print mb.network information to the console
print.mb.nodesplit | Prints basic results from a node-split to the console
print.mb.predict | Print summary information from an mb.predict object
print.mb.rank | Prints a summary of rankings for each parameter
radian.rescale | Calculate position of label with respect to vertex location within a circle
rank | Set rank as a method
rank.mbnma | Rank parameters from a time-course MBNMA
rankauc | Calculates ranking probabilities for AUC from a time-course MBNMA
ref.comparisons | Identify unique comparisons relative to study reference treatment within a network
ref.synth | Synthesise single arm studies with repeated observations of the same treatment over time
ref.validate | Checks the validity of ref.resp if given as data frame
replace.prior | Replace original priors in an MBNMA model with new priors
summary.mb.nodesplit | Takes node-split results and produces summary data frame
summary.mb.predict | Prints summary of mb.predict object
summary.mbnma | Print summary MBNMA results to the console
time.fun | Write time-course function component of JAGS code for MBNMA time-course models
timeplot | Plot raw responses over time by treatment or class
write.alpha | Adds sections of JAGS code for an MBNMA model that correspond to alpha parameters
write.beta | Adds sections of JAGS code for an MBNMA model that correspond to beta parameters
write.check | Checks validity of arguments for mb.write
write.cor | Adds correlation between time-course relative effects
write.fract.poly | Adds additional sections of JAGS code for an MBNMA model required for models with a fractional polynomial time-course
write.inserts | Writes insert points for RegEx in MBNMA JAGS code
write.likelihood | Adds sections of JAGS code for an MBNMA model that correspond to the likelihood
write.model | Write the basic JAGS model code for MBNMA to which other lines of model code can be added
write.piece.fract | Adds additional sections of JAGS code for an MBNMA model required for models with a piecewise linear or fractional polynomial time-course
write.piecelinear | Adds additional sections of JAGS code for an MBNMA model required for models with a piecewise linear time-course
write.ref.synth | Write MBNMA time-course models JAGS code for synthesis of studies investigating reference treatment
write.remove.loops | Removes any loops from MBNMA model JAGS code that do not contain any expressions