Pseudo-observations in survival analysis
PK Andersen, M Pohar Perme - Statistical methods in …, 2010 - journals.sagepub.com
We review recent work on the application of pseudo-observations in survival and event
history analysis. This includes regression models for parameters like the survival function in …
history analysis. This includes regression models for parameters like the survival function in …
A proportional hazards model for the subdistribution of a competing risk
JP Fine, RJ Gray - Journal of the American statistical association, 1999 - Taylor & Francis
With explanatory covariates, the standard analysis for competing risks data involves
modeling the cause-specific hazard functions via a proportional hazards assumption …
modeling the cause-specific hazard functions via a proportional hazards assumption …
[BOOK][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 …
Tutorial in biostatistics: competing risks and multi‐state models
Standard survival data measure the time span from some time origin until the occurrence of
one type of event. If several types of events occur, a model describing progression to each of …
one type of event. If several types of events occur, a model describing progression to each of …
[CITATION][C] Survival and Event History Analysis: A Process Point of View
OO Aalen - 2008 - books.google.com
Time-to-event data are ubiquitous in fields such as medicine, biology, demography,
sociology, economics and reliability theory. Recently, a need to analyze more complex event …
sociology, economics and reliability theory. Recently, a need to analyze more complex event …
Adjusting for nonignorable drop-out using semiparametric nonresponse models
Consider a study whose design calls for the study subjects to be followed from enrollment
(time t= 0) to time t= T, at which point a primary endpoint of interest Y is to be measured. The …
(time t= 0) to time t= T, at which point a primary endpoint of interest Y is to be measured. The …
[BOOK][B] The statistical analysis of interval-censored failure time data
J Sun - 2006 - Springer
Survival analysis, the analysis of failure time data, is a rapid develo** area and a number
of books on the topic have been published in last twenty-five years. However, all of these …
of books on the topic have been published in last twenty-five years. However, all of these …
[BOOK][B] Competing risks and multistate models with R
J Beyersmann, A Allignol, M Schumacher - 2011 - books.google.com
This book covers competing risks and multistate models, sometimes summarized as event
history analysis. These models generalize the analysis of time to a single event (survival …
history analysis. These models generalize the analysis of time to a single event (survival …
[BOOK][B] Accelerated life models: modeling and statistical analysis
V Bagdonavicius, M Nikulin - 2001 - taylorfrancis.com
The authors of this monograph have developed a large and important class of survival
analysis models that generalize most of the existing models. In a unified, systematic …
analysis models that generalize most of the existing models. In a unified, systematic …
A general theory of hypothesis tests and confidence regions for sparse high dimensional models
A general theory of hypothesis tests and confidence regions for sparse high dimensional
models Page 1 The Annals of Statistics 2017, Vol. 45, No. 1, 158–195 DOI: 10.1214/16-AOS1448 …
models Page 1 The Annals of Statistics 2017, Vol. 45, No. 1, 158–195 DOI: 10.1214/16-AOS1448 …