8606 2022 eng 395 407 4 64 article 0 -- -- -- In many applications, geodesic hierarchical models are adequate for the study of temporal observations. We employ such a model derived for manifold-valued data to Kendall's shape space. In particular, instead of the Sasaki metric, we adapt a functional-based metric, which increases the computational efficiency and does not require the implementation of the curvature tensor. We propose the corresponding variational time discretization of geodesics and employ the approach for longitudinal analysis of 2D rat skulls shapes as well as 3D shapes derived from an imaging study on osteoarthritis. Particularly, we perform hypothesis test and estimate the mean trends. Journal of Mathematical Imaging and Vision 10.1007/s10851-022-01079-x yes 2022-02-24 publish urn:nbn:de:0297-zib-85187 Esfandiar Nava-Yazdani Christoph von Tycowicz Hans-Christian Hege Christoph von Tycowicz Visual Data Analysis Hege, Hans-Christian Tycowicz, Christoph von Navayazdani, Esfandiar ECMath-CH15 MathPlus-EF2-3 Visual and Data-centric Computing DDESAMT