 Information loss from censoring in rank-based proceduresJohan Lim, Sungim Lee and Hyungwon Choi Statistics & Probability Letters, 2006, vol. 76, issue 16, 1705-1713 Abstract: Although the problems of measuring information based on entropy are well explored, a few studies have applied to the loss of information from censoring in the survival data. The censoring inherently causes loss of information and, following Lindley's suggestion (1956), the degree of loss in information has been measured by relative change in entropy between experiments with censoring and without censoring, that is, with complete data. In this paper, we propose new indices of quantifying information loss through Fisher information and relative efficiency. It is shown that these indices are asymptotically equivalent to each other, in particular to the entropy-based measure. All these indices will then be used to measure the information loss in ranks or rank-based statistics which is commonly considered in the survival data analysis rather than direct measurements. Evaluation of the indices is also provided for a variety of examples. Keywords: Entropy; Fisher; information; Information; loss; Kendall's; [tau]; Partial; likelihood; Rank; statistics; Relative; efficiency (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:16:p:1705-1713 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 |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.