| 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 |
| binplot |
Plot relative effects from NMAs performed at multiple time-bins |
| 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 |
| default.priors |
Sets default priors for JAGS model code |
| devplot |
Plot deviance contributions from an MBNMA model |
| diabetes |
Studies comparing treatments for type 2 diabetes |
| fitplot |
Plot fitted values from MBNMA model |
| gen.parameters.to.save |
Automatically generate parameters to save for a time-course MBNMA model |
| genmaxcols |
Get large vector of distinct colours using Rcolorbrewer |
| genspline |
Generates spline basis matrices for fitting to time-course function |
| get.closest.time |
Create a dataset with a single time point from each study closest to specified time |
| 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 |
| hyalarthritis |
Studies comparing hyaluronan (HA)–based viscosupplements for osteoarthritis |
| 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 effects 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 |
| tfpoly |
Fractional polynomial time-course function |
| timeplot |
Plot raw responses over time by treatment or class |
| titp |
Integrated Two-Component Prediction (ITP) function |
| 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 |
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