diabetes

An example of network meta-analysis for binary outcomes with follow-up times reported.

dataset

Performs Bayesian arm-based network meta-analysis for datasets with binary, continuous, and count outcomes
(Zhang et al., 2014 <doi:10.1177/1740774513498322>;
Lin et al., 2017 <doi:10.18637/jss.v080.i05>).

Lifeng Lin

pcnetmeta

Patient-Centered Network Meta-Analysis

Jing Zhang

Haitao Chu

diabetes function

A data frame containing 22 studies which compare a total of 6 treatments. The outcome is binary; the mean follow-up time in each study is collected.<dl>
 <dt><code>s.id</code></dt>
<dd>a numeric vector of study IDs.</dd> <dt><code>folup</code></dt>
<dd>a numeric vector of follow-up time (in years) for each study.</dd> <dt><code>t.id</code></dt>
<dd>a numeric vector of treatment IDs.</dd> <dt><code>r</code></dt>
<dd>a numeric vector of the total mortality in each treatment group in each study.</dd> <dt><code>n</code></dt>
<dd>a numeric vector of the total number of participants in each treatment group in each study.</dd> 
</dl>

Format

Network Meta-Ananlysis on Diabetes — diabetes

A data frame containing 22 studies which compare a total of 6 treatments. The outcome is binary; the mean follow-up time in each study is collected.<dl>
 <dt><code>s.id</code></dt>
<dd>a numeric vector of study IDs.</dd>

 <dt><code>folup</code></dt>
<dd>a numeric vector of follow-up time (in years) for each study.</dd>

 <dt><code>t.id</code></dt>
<dd>a numeric vector of treatment IDs.</dd>

 <dt><code>r</code></dt>
<dd>a numeric vector of the total mortality in each treatment group in each study.</dd>

 <dt><code>n</code></dt>
<dd>a numeric vector of the total number of participants in each treatment group in each study.</dd>

 
</dl>

diabetes: Network Meta-Ananlysis on Diabetes

Description

Usage

Arguments

Format

Details