Senn2013

Network meta-analysis in diabetes comparing effects of a number of
drugs on the HbA1c value.
These data are used as an example in Senn et al. (2013) and have been
preprocessed for use in R package netmeta.

datasets

A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis":
- frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>;
- additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>;
- network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>;
- rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>;
- ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) <doi:10.1186/s12874-015-0060-8>;
- split direct and indirect evidence to check consistency (Dias et al., 2010) <doi:10.1002/sim.3767>, (Efthimiou et al., 2019) <doi:10.1002/sim.8158>;
- league table with network meta-analysis results;
- 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <doi:10.1002/jrsm.57>;
- net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <doi:10.1186/1471-2288-13-35>;
- measures characterizing the flow of evidence between two treatments by König et al. (2013) <doi:10.1002/sim.6001>;
- automated drawing of network graphs described in Rücker & Schwarzer (2016) <doi:10.1002/jrsm.1143>;
- partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <doi:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <doi:10.1002/jrsm.1270>;
- contribution matrix as described in Papakonstantinou et al. (2018) <doi:10.12688/f1000research.14770.3> and Davies et al. (2022) <doi:10.1002/sim.9346>;
- network meta-regression with a single continuous or binary covariate;
- subgroup network meta-analysis.

Guido Schwarzer

netmeta

Network Meta-Analysis using Frequentist Methods

Gerta Rücker

Ulrike Krahn

Jochem König

Orestis Efthimiou

Annabel Davies

Theodoros Papakonstantinou

Theodoros Evrenoglou

Krzysztof Ciomek

Nana-Adjoa Kwarteng

Senn2013 function

A data frame with the following columns:<table class="table">
<tr><td>TE</td><td>treatment effect</td></tr>
<tr><td>seTE</td><td>standard error of treatment effect</td></tr>
<tr><td>treat1</td><td>treatment 1</td></tr>
<tr><td>treat2</td><td>treatment 2</td></tr>
<tr><td>treat1.long</td><td>treatment 1 (full treatment names)</td></tr>
<tr><td>treat2.long</td><td>treatment 2 (full treatment names)</td></tr>
<tr><td>studlab</td><td>Study label</td></tr>
</table>

Format

Network meta-analysis in diabetes — Senn2013

A data frame with the following columns:<table class='table'>
<tr><td>TE</td><td>treatment effect</td></tr>
<tr><td>seTE</td><td>standard error of treatment effect</td></tr>
<tr><td>treat1</td><td>treatment 1</td></tr>
<tr><td>treat2</td><td>treatment 2</td></tr>
<tr><td>treat1.long</td><td>treatment 1 (full treatment names)</td></tr>
<tr><td>treat2.long</td><td>treatment 2 (full treatment names)</td></tr>
<tr><td>studlab</td><td>Study label</td></tr>
</table>

Network meta-analysis in diabetes

Senn2013: Network meta-analysis in diabetes

Description

Arguments

Format

Details

See Also

Examples

TE	treatment effect
*seTE*	standard error of treatment effect
*treat1*	treatment 1
*treat2*	treatment 2
*treat1.long*	treatment 1 (full treatment names)
*treat2.long*	treatment 2 (full treatment names)
*studlab*	Study label