title: Rank-based testing of equal survivorship based on cross-sectional survival data with or without prospective follow-up.
abstract: Existing linear rank statistics cannot be applied to cross-sectional survival data without follow-up since all subjects are essentially censored. However, partial survival information are available from backward recurrence times and are frequently collected from health surveys without prospective follow-up. Under length-biased sampling, a class of linear rank statistics is proposed based only on backward recurrence times without any prospective follow-up. When follow-up data are available, the proposed rank statistic and a conventional rank statistic that utilizes follow-up information from the same sample are shown to be asymptotically independent. We discuss four ways to combine these two statistics when follow-up is present. Simulations show that all combined statistics have substantially improved power compared with conventional rank statistics, and a Mantel-Haenszel test performed the best among the proposal statistics. The method is applied to a cross-sectional health survey without follow-up and a study of Alzheimer's disease with prospective follow-up.
authors: Department of Biostatistics, University of Washington, Seattle, WA 98195, USA kcgchan@uw.edu.
authors: Kwun Chuen Gary
authors: KC
authors: Chan
authors: Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA.
authors: Jing
authors: J
authors: Qin
mesh_terms: D000544:Alzheimer Disease; D035843:Biomedical Research / Q000379:methods*; D003430:Cross-Sectional Studies; D003627:Data Interpretation, Statistical; D005500:Follow-Up Studies; D006306:Health Surveys; D006801:Humans; D016019:Survival Analysis
keywords: Accelerated failure time model; Backward recurrence time; Length biased sampling