Abstract This paper describes the first implementation of a new diagnostic analysis model in which a number of previously separate diagnostic models are integrated into a single comprehensive model. The linkage of information from these different models is done using Bayesian probability theory, which allows information about physical parameters inferred from one separate model to be utilised without losses in another model. Since interdependencies between diagnostic models are common for fusion diagnostics, inference of physical parameters from several diagnostic models treated as a whole can be expected to give an increase in accuracy and robustness. One major interdependency between diagnostic models is the common mapping to a magnetic coordinate system, which itself has to be inferred from measurements. Here a fast self-consistent 3D stellarator equilibrium calculation based on function parameterization is used as part of the overall integrated model, which additionally includes a Nd:YAG Thomson scattering system, diamagnetic loop measurement and microwave interferometer. The self-consistent inclusion of a magnetic coordinate reconstruction adds influences from uncertainties in the position of inferred flux surfaces to quantities such as ne-, Te- and pressure profiles. From the reconstructed magnetic mapping itself error bars on quantities like effective radius, iota profiles and plasma volume can be derived. These error bars will reflect both statistical and systematic uncertainties from the whole system.