mtrank-package {mtrank} | R Documentation |
mtrank: Brief overview
Description
R package mtrank enables the estimation of treatment hierarchies in network meta-analysis using a novel frequentist approach based on treatment choice criteria (TCC) and probabilistic ranking models, as described by Evrenoglou et al. (2024). The TCC are defined using a rule based on the smallest worthwhile difference (SWD). Using the defined TCC, the NMA estimates (i.e., treatment effects and standard errors) are first transformed into treatment preferences, indicating either a treatment preference (e.g., treatment A > treatment B) or a tie (treatment A = treatment B). These treatment preferences are then synthesized using a probabilistic ranking model, which estimates the latent ability parameter of each treatment and produces the final treatment hierarchy. This parameter represents each treatments ability to outperform all the other competing treatments in the network. Here the terms "ability to outperform" indicates the propensity of each treatment to yield clinically important and beneficial effects when compared to all the other treatments in the network. Consequently, larger ability estimates indicate higher positions in the ranking list.
Details
The R package mtrank provides the following functions:
Function
tcc
defines the TCC and produces a treatment preference format based on network meta-analysis estimates.Function
mtrank
synthesizes the output of thetcc
function and estimates the final treatment ability.Forest plots are created either for the results of the TCC (
forest.tcc
) or the final ability estimates (forest.mtrank
).Function
fitted.mtrank
uses the ability estimates obtained frommtrank
to calculate pairwise probabilities that any treatment 'A' can be better, equal, or worse than any other treatment 'B' in the network.The function
linegraph
visualizes the output ofmtrank
across different SWD values. It serves as a sensitivity analysis to the initial choice of SWD.
Type help(package = "mtrank")
for a listing of R functions
available in mtrank.
Type citation("mtrank")
on how to cite mtrank
in publications.
To report problems and bugs, please send an email to Theodoros Evrenoglou <theodoros.evrenoglou@uniklinik-freiburg.de>.
The development version of mtrank is available on GitHub https://github.com/TEvrenoglou/mtrank.
Author(s)
Theodoros Evrenoglou <theodoros.evrenoglou@uniklinik-freiburg.de>, Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>
References
Evrenoglou T, Nikolakopoulou A, Schwarzer G, Rücker G, Chaimani A (2024): Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria, https://arxiv.org/abs/2406.10612
See Also
Useful links: