{"doi":"10.5705/ss.202024.0003","title":"Rank-Based Inference for the Accelerated Failure Time Model with Partially Interval-Censored Data","abstract":"This paper presents a unified rank-based inferential procedure for fitting the accelerated failure time model to partially interval-censored data.A Gehantype monotone estimating function is constructed based on the idea of the familiar weighted log-rank test, and an extension to a general class of rank-based estimating functions is suggested.The proposed estimators can be obtained via linear programming and are shown to be consistent and asymptotically normal via standard empirical process theory.Unlike common maximum likelihood-based estimators for partially interval-censored regression models, our approach can directly provide a regression coefficient estimator without involving a complex nonparametric estimation of the underlying residual distribution function.An efficient variance estimation procedure for the regression coefficient estimator is considered.Moreover, we extend the proposed rank-based procedure to the linear regression analysis of multivariate clustered partially interval-censored data.The finite-sample operating characteristics of our approach are examined via simulation studies.Data example from a colorectal cancer study illustrates the practical usefulness of the method.","journal":"Statistica Sinica","year":2025,"id":561565,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9513,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":390941,"name":"Sangbum Choi","orcid":"0000-0001-6983-5821","position":1,"is_corresponding":false},{"id":1053239,"name":"Dipankar Bandyopadhyay","orcid":"0000-0002-9703-5300","position":2,"is_corresponding":false},{"id":740954,"name":"Taehwa Choi","orcid":"0000-0001-7750-9276","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:55:58.259104Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}