%0 Generic %A Seide, Svenja Elisabeth %A Jensen, Katrin %A Kieser, Meinhard %D 2019 %T Dataset for: Simulation and data-generation for random-effects network meta-analysis of binary outcome %U https://wiley.figshare.com/articles/dataset/Dataset_for_Simulation_and_data-generation_for_random-effects_network_meta-analysis_of_binary_outcome/8001863 %R 10.6084/m9.figshare.8001863.v1 %2 https://wiley.figshare.com/ndownloader/files/14902799 %K random-effects network meta-analysis %K binary data %K data-generating model %K multi-arm trials %K simulation %K Statistics %K Medicine %X The performance of statistical methods is frequently evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, available data- generating models are restricted to either inclusion of two-armed trials or the fixed-effect model. Based on data-generation in the pairwise case, we propose a framework for the simulation of random-effect network meta-analyses including multi-arm trials with binary outcome. The only of the common data-generating models which is directly applicable to a random-effects network setting uses strongly restrictive assumptions. To overcome these limitations, we modify this approach and derive a related simulation procedure using odds ratios as effect measure. The performance of this procedure is evaluated with synthetic data and in an empirical example. %I Wiley