| 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 |
| copd | Studies comparing Tiotropium, Aclidinium and Placebo for maintenance treatment of moderate to severe chronic obstructive pulmonary disease |
| cumrank | Plot cumulative ranking curves from MBNMA models |
| 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 |
| genspline | Generates spline basis matrices for fitting to time-course function |
| 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 |
| get.relative | Calculates relative effects/mean differences at a particular time-point |
| getjagsdata | Prepares data for JAGS |
| getnmadata | Prepares NMA 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 fulfil criteria for node-splitting |
| mb.comparisons | Identify unique comparisons within a network (identical to MBNMAdose) |
| 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 fulfil criteria for node-splitting |
| 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 fulfils requirements for MBNMA |
| mb.write | Write MBNMA time-course models JAGS code |
| nma.run | Run an NMA model |
| 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.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 |
| plot.nodesplit | Perform node-splitting on a MBNMA time-course network |
| 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.predict | Print summary information from an mb.predict object |
| print.mb.rank | Prints a summary of rankings for each parameter |
| print.nodesplit | Prints basic results from a node-split to the console |
| print.relative.array | Print posterior medians (95% credible intervals) for table of relative effects/mean differences between treatments/classes |
| radian.rescale | Calculate position of label with respect to vertex location within a circle |
| rank | Set rank as a method |
| rank.mb.predict | Rank predictions at a specific time point |
| 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 |
| remove.loops | Removes any loops from MBNMA model JAGS code that do not contain any expressions |
| replace.prior | Replace original priors in an MBNMA model with new priors |
| summary.mb.network | Print summary mb.network information to the console |
| summary.mb.predict | Prints summary of mb.predict object |
| summary.mbnma | Print summary MBNMA results to the console |
| summary.nodesplit | Takes node-split results and produces summary data frame |
| temax | Emax time-course function |
| texp | Exponential time-course function |
| tfpoly | Fractional polynomial time-course function |
| timeplot | Plot raw responses over time by treatment or class |
| tloglin | Log-linear (exponential) time-course function |
| tpoly | Polynomial time-course function |
| tspline | Spline time-course functions |
| tuser | User-defined time-course function |
| 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.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.ref.synth | Write MBNMA time-course models JAGS code for synthesis of studies investigating reference treatment |
| write.timecourse | Adds sections of JAGS code for an MBNMA model that correspond to alpha parameters |