heartfailure

A network meta-analysis data from Sciarretta et al. (2011) that compared 7 antihypertensive drug classes and placebo for occurrence of heart failure.<ul>
<li><code>study</code>: Study ID</li>
<li><code>trial</code>: Trial name</li>
<li><code>trt</code>: Treatment (AB (Alpha blocker), ACE (ACE inhibitor), ARB, BB (Beta blocker), CCB (Calcium-channel blocker), CT (conventional treatments), Diuretic (DD), Placebo)</li>
<li><code>n</code>: Sample size</li>
<li><code>d</code>: Number of events (occurrence of heart failure)</li>
<li><code>pubyear</code>: Publication year</li>
<li><code>SBP</code>: Mean of baseline systolic blood pressure (mmHg)</li>
<li><code>DBP</code>: Mean of diastolic systolic blood pressure (mmHg)</li>
</ul>

datasets

Network meta-analysis tools based on contrast-based approach using the multivariate meta-analysis and meta-regression models (Noma et al. (2025) <doi:10.1101/2025.09.15.25335823>). Comprehensive analysis tools for network meta-analysis and meta-regression (e.g., synthesis analysis, ranking analysis, and creating league table) are available through simple commands. For inconsistency assessment, the local and global inconsistency tests based on the Higgins' design-by-treatment interaction model are available. In addition, the side-splitting methods and Jackson's random inconsistency model can be applied. Standard graphical tools for network meta-analysis, including network plots, ranked forest plots, and transitivity analyses, are also provided. For the synthesis analyses, the Noma-Hamura's improved REML (restricted maximum likelihood)-based methods (Noma et al. (2023) <doi:10.1002/jrsm.1652> <doi:10.1002/jrsm.1651>) are adopted as the default methods.

heartfailure: Sciarretta et al. (2011)'s network meta-analysis data

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