{"paper":{"title":"Post-Selection Inference for Multiverse Analysis in Mixed-Effects Models (PIMAX)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Angela Andreella, Anna Vesely","submitted_at":"2026-07-03T11:39:14Z","abstract_excerpt":"Sign-flipping score tests provide robust inference in generalized linear models under variance misspecification and form the basis of two recent inferential frameworks: post-selection inference in multiverse analysis (PIMA) and the sign-flipping score-based two-stage summary-statistics approach (flip2sss). PIMA provides asymptotically valid inference across a multiverse of model specifications, whereas flip2sss extends sign-flipping score testing to longitudinal and hierarchical data through cluster-level summary statistics. In this paper, we combine these two approaches to develop PIMAX, a mu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.03225","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.03225/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"}