The statistical analysis of doubly truncated data : with applications in R / Jacobo de Uña-Álvarez, Carla Moreira, Rosa M. Crujeiras

"This book is the result of a long-standing collaboration among the three authors, which began when Carla Moreira was a PhD student under the supervision of Jacobo de Unã-Álvarez. Carla successfully defended her thesis, entitled 'The Statistical Analysis of Doubly Truncated Data: New Methods, Software Development, and Biomedical Applications', at the Universidade de Vigo in July 2010. At that time, just a reduced group of people seemed to be aware of the importance of random double truncation. Research papers on this topic were scarce before 2010, with the contribution by Bradley Efron and Vahe Petrosian in 1999 as the most relevant one. And, of course, no software was available. So, for us, it was a risky and exciting research exercise to embrace such an initiative. This book aims to serve as a companion for those ones interested in learning about doubly truncated data analysis and inference, presenting a wide range of tools for estimating distribution and regression models. All the methods presented in this book are accompanied by real data and simulated examples and, at the end of each chapter, the reader will find the do-it-yourself code, mostly based on DTDA package. This book is not written with the aim of being just read: its main purpose is to invite the reader to think, explore and experience"--.

Medienart:

E-Book

Erscheinungsjahr:

2022

Erschienen:

Hoboken, NJ: Wiley ; 2022

Reihe:

Wiley series in probability and statistics

Sprache:

Englisch

Beteiligte Personen:

Uña-Álvarez, Jacobo de, 1972- [VerfasserIn]
Moreira, Carla, 1972- [VerfasserIn]
Crujeiras, Rosa María, 1978- [VerfasserIn]

Links:

doi.org [lizenzpflichtig]
onlinelibrary.wiley.com [lizenzpflichtig]

ISBN:

978-1-119-50047-6

1-119-50047-8

978-1-119-50048-3

1-119-50048-6

978-1-119-50046-9

1-119-50046-X

Nlm:

QH 323.5

Themen:

Biometry
Data Interpretation, Statistical
Electronic books
Methods (Music)
Models, Statistical
Programming Languages
R (Computer program language)
Statistics
Statistics - Computer programs
Statistics as Topic

Anmerkungen:

Includes bibliographical references and index

Umfang:

1 Online-Ressource

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

1797148338