This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.
"synopsis" may belong to another edition of this title.
Dr. Jong-Hyeon Jeong is a full professor of Biostatistics at the University of Pittsburgh. Dr. Jeong's main research area has been survival analysis and clinical trials. In survival analysis, he has worked on frailty modeling, efficiency of survival probability estimates from the proportional hazards model, weighted log-rank test, competing risks, quantile residual life, and likelihood theory such as empirical likelihood and hierarchical likelihood. In clinical trials, he has been involved in several phase III clinical trials on breast cancer treatment as the primary statistician. He has been teaching statistical theory courses and survival analysis in the Department of Biostatistics at the University of Pittsburgh. Dr. Jeong holds his PhD degree in statistics from the University of Rochester and has been an elected member of the International Statistical Institute (ISI) since 2007.
This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.
"About this title" may belong to another edition of this title.
£ 14.88 shipping from U.S.A. to United Kingdom
Destination, rates & speeds£ 2.40 shipping from Italy to United Kingdom
Destination, rates & speedsSeller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Questo è un articolo print on demand. Seller Inventory # c6079a547ae420c647c15d2c046ccffd
Quantity: Over 20 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9781493900046_new
Quantity: Over 20 available
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 598. Seller Inventory # C9781493900046
Quantity: Over 20 available
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book. 216 pp. Englisch. Seller Inventory # 9781493900046
Quantity: 2 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 20583652-n
Quantity: 15 available
Seller: Best Price, Torrance, CA, U.S.A.
Condition: New. SUPER FAST SHIPPING. Seller Inventory # 9781493900046
Quantity: 2 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book. Seller Inventory # 9781493900046
Quantity: 1 available
Seller: moluna, Greven, Germany
Condition: New. Seller Inventory # 4213611
Quantity: Over 20 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 20583652
Quantity: 15 available
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: New. Statistical Inference on Residual Life Series: Statistics for Biology and Health. Num Pages: 212 pages, 5 black & white illustrations, 12 colour illustrations, 10 black & white tables. BIC Classification: MBNS; PBT; PSA. Category: (P) Professional & Vocational. Dimension: 243 x 164 x 14. Weight in Grams: 452. . 2014. 2014th Edition. Hardcover. . . . . Seller Inventory # V9781493900046
Quantity: 15 available