Author: Rudolf J. BeranPublisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 38
Book Description
Nonparametric Regression with Randomly Censored Survival Data
Author: Rudolf J. BeranPublisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 38
Book Description
Nonparametric Regression with Censored Survival Time Data
Author: D. M. DabrowskaSurvival Analysis
Author: Rupert G. Miller, Jr.Publisher: John Wiley & Sons
ISBN: 1118031067
Category : Mathematics
Languages : en
Pages : 254
Book Description
A concise summary of the statistical methods used in the analysis of survival data with censoring. Emphasizes recently developed nonparametric techniques. Outlines methods in detail and illustrates them with actual data. Discusses the theory behind each method. Includes numerous worked problems and numerical exercises.
Missing and Modified Data in Nonparametric Estimation
Author: Sam EfromovichPublisher: CRC Press
ISBN: 135167983X
Category : Mathematics
Languages : en
Pages : 867
Book Description
This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.
Robust Nonparametric Regression Approach for Competing Cause Censored Survival Mortality Data with Covariates
Author: Milind A. PhadnisNonparametric Regression for Censored and Truncated Data
Author: Chul-Ki KimNonparametric and Semiparametric Censored Survival Analysis of Correlated Times to Event and Their Sequelae
Author: Adin-Cristian AndreiPublisher:
ISBN:
Category :
Languages : en
Pages : 194
Book Description
Analysis of Censored Data
Author: Hira L. KoulPublisher: IMS
ISBN: 9780940600393
Category : Censored observations (Statistics)
Languages : en
Pages : 310
Book Description
Survival Analysis Using S
Author: Mara TablemanPublisher: CRC Press
ISBN: 0203501411
Category : Mathematics
Languages : en
Pages : 277
Book Description
Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter written by Stephen Portnoy, censored regression quantiles - a new nonparametric regression methodology (2003) - is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the Kaplan-Meier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.
Analysis of Survival Data
Author: D.R. CoxPublisher: Routledge
ISBN: 1351466607
Category : Mathematics
Languages : en
Pages : 216
Book Description
This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.