[图书][B] Dynamic regression models for survival data
T Martinussen, TH Scheike - 2006 - Springer
Dynamic Regression Models for Survival Data | SpringerLink Skip to main content
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Advertisement SpringerLink Log in Menu Find a journal Publish with us Search Cart Book cover …
Understanding the Cox regression models with time-change covariates
M Zhou - The American Statistician, 2001 - Taylor & Francis
The Cox regression model is a cornerstone of modern survival analysis and is widely used
in many other fields as well. But the Cox models with time-change covariates are not easy to …
in many other fields as well. But the Cox models with time-change covariates are not easy to …
Extensions and applications of the Cox-Aalen survival model
TH Scheike, MJ Zhang - Biometrics, 2003 - academic.oup.com
Cox's regression model is the standard regression tool for survival analysis in most
applications. Often, however, the model only provides a rough summary of the effect of some …
applications. Often, however, the model only provides a rough summary of the effect of some …
Tutorial: survival estimation for Cox regression models with time-varying coefficients using SAS and R
L Thomas, EM Reyes - Journal of Statistical Software, 2014 - jstatsoft.org
Survival estimates are an essential compliment to multivariable regression models for time-
to-event data, both for prediction and illustration of covariate effects. They are easily …
to-event data, both for prediction and illustration of covariate effects. They are easily …
[引用][C] Modeling Survival Data: Extending the Cox Model. Terry M. Therneau and Patricia M. Grambsch, Springer‐Verlag, New York, 2000. No. of pages: xiii+ 350 …
Ø Borgan - 2001 - Wiley Online Library
The book is divided into ten chapters. In addition come five appendices which give useful
introductions to the SAS and S-plus software and describe the SAS macros, S-plus functions …
introductions to the SAS and S-plus software and describe the SAS macros, S-plus functions …
[PDF][PDF] Cox proportional-hazards regression for survival data
J Fox, S Weisberg - An R and S-PLUS companion to applied …, 2002 - gilbertresearch.org
Survival analysis examines and models the time it takes for events to occur, termed survival
time. The Cox proportional-hazards regression model is the most common tool for studying …
time. The Cox proportional-hazards regression model is the most common tool for studying …
Weighted Cox regression using the R package coxphw
Cox's regression model for the analysis of survival data relies on the proportional hazards
assumption. However, this assumption is often violated in practice and as a consequence …
assumption. However, this assumption is often violated in practice and as a consequence …
[HTML][HTML] Time-varying covariates and coefficients in Cox regression models
Time-varying covariance occurs when a covariate changes over time during the follow-up
period. Such variable can be analyzed with the Cox regression model to estimate its effect …
period. Such variable can be analyzed with the Cox regression model to estimate its effect …
[图书][B] The cox model
TM Therneau, PM Grambsch, TM Therneau… - 2000 - Springer
The Cox Model Page 1 3 The Cox Model 3.1 Introduction and notation The Cox proportional
hazards model [36] has become by a wide margin the most used procedure for modeling the …
hazards model [36] has become by a wide margin the most used procedure for modeling the …
An approach to estimation in relative survival regression
MP Perme, R Henderson, J Stare - Biostatistics, 2009 - academic.oup.com
The goal of relative survival methodology is to compare the survival experience of a cohort
with that of the background population. Most often an additive excess hazard model is …
with that of the background population. Most often an additive excess hazard model is …