diabetes

Network meta-analysis comparing six antihypertensive drugs against the
incidence of diabetes.

datasets

Implementation of a novel frequentist approach to produce clinically relevant treatment hierarchies in network meta-analysis. The method is based on treatment choice criteria (TCC) and probabilistic ranking models, as described by Evrenoglou et al. (2024) <DOI:10.48550/arXiv.2406.10612>. The TCC are defined using a rule based on the minimal clinically important difference. Using the defined TCC, the study-level data (i.e., treatment effects and standard errors) are first transformed into a preference format, indicating either a treatment preference (e.g., treatment A > treatment B) or a tie (treatment A = treatment B). The preference data 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 treatment’s ability to outperform all the other competing treatments in the network. Consequently, larger ability estimates indicate higher positions in the ranking list.

Theodoros Evrenoglou

mtrank

Ranking using Probabilistic Models and Treatment Choice Criteria

Guido Schwarzer

diabetes function

A data frame with the following columns:<table class="table">
<tr><td>study</td><td>study label</td></tr>
<tr><td>id</td><td>study id</td></tr>
<tr><td>t</td><td>treatment label</td></tr>
<tr><td>r</td><td>number of events</td></tr>
<tr><td>n</td><td>group sample size</td></tr>
<tr><td>rob</td><td>risk of bias assessment</td></tr>
</table>

Format

Network meta-analysis studying the incidence of diabetes — diabetes

A data frame with the following columns:<table class='table'>
<tr><td>study</td><td>study label</td></tr>
<tr><td>id</td><td>study id</td></tr>
<tr><td>t</td><td>treatment label</td></tr>
<tr><td>r</td><td>number of events</td></tr>
<tr><td>n</td><td>group sample size</td></tr>
<tr><td>rob</td><td>risk of bias assessment</td></tr>
</table>

diabetes: Network meta-analysis studying the incidence of diabetes

Description

Arguments

Format

See Also

Examples

*study*	study label
id	study id
t	treatment label
r	number of events
n	group sample size
*rob*	risk of bias assessment