title: Pseudo-value approach for comparing survival medians for dependent data.
abstract: Survival median is commonly used to compare treatment groups in cancer-related research. The current literature focuses on developing tests for independent survival data. However, researchers often encounter dependent survival data such as matched pair data or clustered data. We propose a pseudo-value approach to test the equality of survival medians for both independent and dependent survival data. We investigate the type I error and power of the proposed method by a simulation study, in which we examine independent and dependent data. The simulation study shows that the proposed method performs equivalently to the existing methods for independent survival data and performs better for dependent survival data. A study comparing survival median times for bone marrow transplants illustrates the proposed method.
authors: Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank RoadMilwaukee, WI, 53226, U.S.A.
authors: Kwang Woo
authors: KW
authors: Ahn
authors: Franco
authors: F
authors: Mendolia
mesh_terms: D016026:Bone Marrow Transplantation; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D016000:Cluster Analysis; D006801:Humans; D009369:Neoplasms / Q000628:therapy; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D013223:Statistics as Topic / Q000379:methods; D016019:Survival Analysis
keywords: censored data; clustered data; pseudo-value approach; survival median