diabetes

A dataset from of trials for reduction of haemoglobin A1c (HbA1c) in patients
with type 2 diabetesdingfu2013MBNMAtime.
Data are reported in each study arm as mean change from baseline to follow-up.
The dataset includes 4 Randomised-Controlled Trials (RCTs), comparing 4 treatments.

datasets

Fits Bayesian time-course models for model-based network meta-analysis (MBNMA) that allows inclusion of multiple
time-points from studies. Repeated measures over time are accounted for within studies by applying different time-course functions,
following the method of Pedder et al. (2019) <doi:10.1002/jrsm.1351>.
The method allows synthesis of studies with multiple follow-up measurements that can account for time-course for a single or multiple
treatment comparisons. Several general time-course functions are provided; others may be added
by the user. Various characteristics can be flexibly added to the models, such as correlation between time points and shared
class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects
models and/or by node-splitting.

Hugo Pedder

MBNMAtime

Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models

diabetes function

A data frame in long format (one row per arm and study), with 28 rows and 7 variables:<ul>
<li><code>studyID</code> Study identifiers</li>
<li><code>treatment</code> Numeric data indicating the treatment to which participants were randomised</li>
<li><code>time</code> Numeric data indicating the time at which the observation was measured (given in weeks)</li>
<li><code>y</code> Numeric data indicating the mean change from baseline in HbA1c in a study arm</li>
<li><code>se</code> Numeric data indicating the standard error for the mean change from baseline in HbA1c in a study arm</li>
<li><code>sd</code> Numeric data indicating the standard deviation for the mean change from baseline in HbA1c in a study arm</li>
<li><code>n</code> Numeric data indicating the number of participants in each arm at each time-point</li>
</ul>

diabetes: Studies comparing treatments for type 2 diabetes

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