 Resolving the tail instability in weighted log-rank statistics for clustered survival dataMichael R. Kosorok and Ronald E. Gangnon Statistics & Probability Letters, 2006, vol. 76, issue 3, 304-309 Abstract: In this note, we consider weighted log-rank statistics applied to clustered survival data with variable cluster sizes and arbitrary treatment assignments within clusters. Specifically, we verify that the contribution over the time interval for which the risk set proportion is arbitrarily small (the so-called "tail instability") is asymptotically negligible. These results were claimed but not proven by Gangnon and Kosorok [2004. Sample-size formula for clustered survival data using weighted log-rank statistics. Biometrika 91, 263-275.] who developed sample size formulas in this context. The main difficulty is that standard martingale methods cannot be used on account of the dependencies within clusters, and new methods are required. Keywords: Clustered; data; Local; alternative; Log-rank; statistic; Martingales; Multivariate; survival; data; Tail; instability (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:76:y:2006:i:3:p:304-309 Ordering information: This journal article can be ordered from Access Statistics for this article Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul More articles in Statistics & Probability Letters from Elsevier |
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