Advanced Survival Models PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Advanced Survival Models PDF full book. Access full book title Advanced Survival Models by Catherine Legrand. Download full books in PDF and EPUB format.
Author: Catherine Legrand
Publisher: CRC Press
ISBN: 0429622554
Category : Mathematics
Languages : en
Pages : 361
Get Book Here
Book Description
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods used in a wide range of applications, and in particular in medical research. During the last twenty years, several extensions of "classical" survival models have been developed to address particular situations often encountered in practice. This book aims to gather in a single reference the most commonly used extensions, such as frailty models (in case of unobserved heterogeneity or clustered data), cure models (when a fraction of the population will not experience the event of interest), competing risk models (in case of different types of event), and joint survival models for a time-to-event endpoint and a longitudinal outcome. Features Presents state-of-the art approaches for different advanced survival models including frailty models, cure models, competing risk models and joint models for a longitudinal and a survival outcome Uses consistent notation throughout the book for the different techniques presented Explains in which situation each of these models should be used, and how they are linked to specific research questions Focuses on the understanding of the models, their implementation, and their interpretation, with an appropriate level of methodological development for masters students and applied statisticians Provides references to existing R packages and SAS procedure or macros, and illustrates the use of the main ones on real datasets This book is primarily aimed at applied statisticians and graduate students of statistics and biostatistics. It can also serve as an introductory reference for methodological researchers interested in the main extensions of classical survival analysis.
Author: Catherine Legrand
Publisher: CRC Press
ISBN: 0429622554
Category : Mathematics
Languages : en
Pages : 361
Get Book Here
Book Description
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods used in a wide range of applications, and in particular in medical research. During the last twenty years, several extensions of "classical" survival models have been developed to address particular situations often encountered in practice. This book aims to gather in a single reference the most commonly used extensions, such as frailty models (in case of unobserved heterogeneity or clustered data), cure models (when a fraction of the population will not experience the event of interest), competing risk models (in case of different types of event), and joint survival models for a time-to-event endpoint and a longitudinal outcome. Features Presents state-of-the art approaches for different advanced survival models including frailty models, cure models, competing risk models and joint models for a longitudinal and a survival outcome Uses consistent notation throughout the book for the different techniques presented Explains in which situation each of these models should be used, and how they are linked to specific research questions Focuses on the understanding of the models, their implementation, and their interpretation, with an appropriate level of methodological development for masters students and applied statisticians Provides references to existing R packages and SAS procedure or macros, and illustrates the use of the main ones on real datasets This book is primarily aimed at applied statisticians and graduate students of statistics and biostatistics. It can also serve as an introductory reference for methodological researchers interested in the main extensions of classical survival analysis.
Author: American Statistical Association
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages :
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages :
Get Book Here
Book Description
Author: L. A. Goodman
Publisher: Springer Science & Business Media
ISBN: 1461299950
Category : Mathematics
Languages : en
Pages : 156
Get Book Here
Book Description
In 1954, prior to the era of modem high speed computers, Leo A. Goodman and William H. Kruskal published the fmt of a series of four landmark papers on measures of association for cross classifications. By describing each of several cross classifications using one or more interpretable measures, they aimed to guide other investigators in the use of sensible data summaries. Because of their clarity of exposition, and their thoughtful statistical approach to such a complex problem, the guidance in this paper is as useful and important today as it was on its publication 25 years ago. in a cross-classification by a single number inevita Summarizing association bly loses information. Only by the thoughtful choice of a measure of association can one hope to lose only the less important information and thus arrive at a satisfactory data summary. The series of four papers reprinted here serve as an outstanding guide to the choice of such measures and their use.
Author: Maura Ellen Stokes
Publisher: Simon and Schuster
ISBN: 1499808127
Category : Juvenile Fiction
Languages : en
Pages : 250
Get Book Here
Book Description
When Sam's best friend Reagan dies after her heart suddenly gives out, Sam must learn to deal with her grief and ultimately discover who she is without her best friend by her side. Fourteen-year-old Sam thinks she has all summer to hang out with her best friend, Reagan. But then her life changes forever. Sam's world, once filled with school, basketball, and Reagan, has now abruptly changed and she must learn to navigate high school on and off the court without her best friend. But when Reagan suddenly "reappears," Sam clings to her friend's presence, even as it hurts rather than helps her grief. Can Sam learn to accept herself without her other half? This authentic, powerful story of friendship, grief, and discovering yourself is a can't-miss debut novel from Maura Ellen Stokes.
Author: Anna Bargagliotti
Publisher:
ISBN: 9781734223514
Category : Statistics
Languages : en
Pages : 124
Get Book Here
Book Description
"This document lays out a curriculum framework for pre-K-12 educational programs that is designed to help students achieve data literacy and become statistically literate. The framework and subsequent sections in this book recommend curriculum and implementation strategies covering pre-K-12 statistics education"--
Author: Bing Li
Publisher: CRC Press
ISBN: 1351645730
Category : Mathematics
Languages : en
Pages : 362
Get Book Here
Book Description
Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field. Features Provides comprehensive coverage of this emerging research field. Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion. Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data. Includes a set of computer codes written in R that are easily implemented by the readers. Uses real data sets available online to illustrate the usage and power of the described methods. Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones. The author Bing Li obtained his Ph.D. from the University of Chicago. He is currently a Professor of Statistics at the Pennsylvania State University. His research interests cover sufficient dimension reduction, statistical graphical models, functional data analysis, machine learning, estimating equations and quasilikelihood, and robust statistics. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is an Associate Editor for The Annals of Statistics and the Journal of the American Statistical Association.
Author: Dani Ben-Zvi
Publisher: Springer Science & Business Media
ISBN: 1402022786
Category : Mathematics
Languages : en
Pages : 423
Get Book Here
Book Description
Unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels, this volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
Author: Arunabh Ghosh
Publisher: Princeton University Press
ISBN: 0691179476
Category : History
Languages : en
Pages : 360
Get Book Here
Book Description
Revision of author's thesis (doctoral)--Columbia University, 2014, titled Making it count: statistics and state-society relations in the early People's Republic of China, 1949-1959.
Author: S. J. Prais
Publisher: CUP Archive
ISBN: 9780521081184
Category : Business & Economics
Languages : en
Pages : 262
Get Book Here
Book Description
Economic research monograph on the statistical analysis and measurement of family budget and income in the UK, based on research results of surveys conducted between 1937 and 1939 - refers in particular to consumer expenditure and household consumption behaviour, describes the theoretics and research methodology of data collecting and calculation (incl. Computer-based computation), data analysis, etc., and discusses implications for future research. References and statistical tables.
