[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 …
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 …
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 …
Evaluating the proportional hazards assumption
DG Kleinbaum, M Klein, DG Kleinbaum… - Survival analysis: a self …, 2012 - Springer
4 Evaluating the Proportional Hazards Assumption Page 1 4 Evaluating the Proportional
Hazards Assumption DG Kleinbaum and M. Klein, Survival Analysis: A Self-Learning Text …
Hazards Assumption DG Kleinbaum and M. Klein, Survival Analysis: A Self-Learning Text …
On the Cox model with time-varying regression coefficients
In the analysis of censored failure time observations, the standard Cox proportional hazards
model assumes that the regression coefficients are time invariant. Often, these parameters …
model assumes that the regression coefficients are time invariant. Often, these parameters …
[图书][B] Applied survival analysis: regression modeling of time-to-event data
THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-
EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition …
EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition …
[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 …
[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
Advertisement SpringerLink Log in Menu Find a journal Publish with us Search Cart Book cover …
Advertisement SpringerLink Log in Menu Find a journal Publish with us Search Cart Book cover …
Predicting the restricted mean event time with the subject's baseline covariates in survival analysis
For designing, monitoring, and analyzing a longitudinal study with an event time as the
outcome variable, the restricted mean event time (RMET) is an easily interpretable, clinically …
outcome variable, the restricted mean event time (RMET) is an easily interpretable, clinically …
The accelerated failure time model: a useful alternative to the Cox regression model in survival analysis
LJ Wei - Statistics in medicine, 1992 - Wiley Online Library
For the past two decades the Cox proportional hazards model has been used extensively to
examine the covariate effects on the hazard function for the failure time variable. On the …
examine the covariate effects on the hazard function for the failure time variable. On the …