Ranking treatments in frequentist network meta-analysis works without resampling methods
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2288
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Ranking treatments in frequentist network meta-analysis works without resampling methods ; volume:15 ; number:1 ; day:31 ; month:7 ; year:2015 ; pages:1-9 ; date:12.2015
BMC medical research methodology ; 15, Heft 1 (31.7.2015), 1-9, 12.2015
- Creator
- Contributor
- DOI
-
10.1186/s12874-015-0060-8
- URN
-
urn:nbn:de:1111-2016110433994
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:44 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Rücker, Gerta
- Schwarzer, Guido
- SpringerLink (Online service)
Other Objects (12)
Ranking treatments in frequentist network meta-analysis works without resampling methods
Presenting simulation results in a nested loop plot
Beyond the forest plot: the drapery plot
Network meta‐analysis of multicomponent interventions
Component network meta‐analysis compared to a matching method in a disconnected network: A case study
LFK index does not reliably detect small‐study effects in meta‐analysis: a simulation study
Network meta‐analysis of multicomponent interventions
Discussion on ‘Testing small study effects in multivariate meta‐analysis’ by Chuan Hong, Georgia Salanti, Sally Morton, Richard Riley, Haitao Chu, Stephen E Kimmel and Yong Chen
Inconsistent results for Peto odds ratios in multi‐arm studies, network meta‐analysis and indirect comparisons
Component network meta‐analysis compared to a matching method in a disconnected network: A case study
Undue reliance on I2 in assessing heterogeneity may mislead
Undue reliance on I2 in assessing heterogeneity may mislead
Ranking treatments in frequentist network meta-analysis works without resampling methods
Presenting simulation results in a nested loop plot
Beyond the forest plot: the drapery plot
Network meta‐analysis of multicomponent interventions
Component network meta‐analysis compared to a matching method in a disconnected network: A case study
LFK index does not reliably detect small‐study effects in meta‐analysis: a simulation study
Network meta‐analysis of multicomponent interventions
Discussion on ‘Testing small study effects in multivariate meta‐analysis’ by Chuan Hong, Georgia Salanti, Sally Morton, Richard Riley, Haitao Chu, Stephen E Kimmel and Yong Chen
Inconsistent results for Peto odds ratios in multi‐arm studies, network meta‐analysis and indirect comparisons
Component network meta‐analysis compared to a matching method in a disconnected network: A case study
Undue reliance on I2 in assessing heterogeneity may mislead
Undue reliance on I2 in assessing heterogeneity may mislead
Ranking treatments in frequentist network meta-analysis works without resampling methods
Presenting simulation results in a nested loop plot
Beyond the forest plot: the drapery plot
Network meta‐analysis of multicomponent interventions
Component network meta‐analysis compared to a matching method in a disconnected network: A case study
LFK index does not reliably detect small‐study effects in meta‐analysis: a simulation study
Network meta‐analysis of multicomponent interventions
Discussion on ‘Testing small study effects in multivariate meta‐analysis’ by Chuan Hong, Georgia Salanti, Sally Morton, Richard Riley, Haitao Chu, Stephen E Kimmel and Yong Chen
Inconsistent results for Peto odds ratios in multi‐arm studies, network meta‐analysis and indirect comparisons
Component network meta‐analysis compared to a matching method in a disconnected network: A case study
Undue reliance on I2 in assessing heterogeneity may mislead