{"paper":{"title":"Bayesian Hierarchical Modeling of Longitudinal Glaucomatous Visual Fields using a Two-Stage Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"B. Li, D. Rizopoulos, E.M.E.H. Lesaffre, H.G. Lemij, K.A. Vermeer, P.H.C. Eilers, S. R. Bryan","submitted_at":"2015-02-13T13:18:47Z","abstract_excerpt":"The Bayesian approach has become increasingly popular because it allows to model quite complex models via Markov chain Monte Carlo (MCMC) sampling. However, it is also recognized nowadays that MCMC sampling can become computationally prohibitive when a complex model needs to be fit to a large data set. To overcome this problem, we applied and extended a recently proposed two-stage approach to model a complex hierarchical data structure of glaucoma patients who participate in an ongoing Dutch study. Glaucoma is one of the leading causes of blindness in the world. In order to detect deterioratio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1502.03979","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}