Tutorial: Survival Analysis--A Statistic for Clinical, Efficacy, and Theoretical Applications
- Dynamic frailty models based on compound birth-death processes. PUTTER, HEIN; VAN HOUWELINGEN, HANS C. // Biostatistics;Jul2015, Vol. 16 Issue 3, p550
Frailty models are used in survival analysis to model unobserved heterogeneity. They accommodate such heterogeneity by the inclusion of a random term, the frailty, which is assumed to multiply the hazard of a subject (individual frailty) or the hazards of all subjects in a cluster (shared...
- Multi-state models. Andersen, PK // Statistical Methods in Medical Research;Apr2002, Vol. 11 Issue 2, p89
Editorial. Comments on the development of the field of survival analysis as an independent statistical discipline. Introduction of the framework for counting processes, martingales and stochastic integrals; Emphasis of the multistate models on medical and epidemiological applications;...
- Erratum. // Statistical Methods in Medical Research;Apr2010, Vol. 19 Issue 2, p200
A correction to the article "Survival analysis with high-dimensional covariates" that was published in the 2010 issue is presented.
- Survival analysis, longitudinal analysis and causal inference. Aalen, Odd // Lifetime Data Analysis;Mar2010, Vol. 16 Issue 1, p1
The author discusses various reports published within the issue including Granger causality by Michael Eichler and Vanessa Didelez, stochastic processes and extending the notion of local independence to a more general concept of influence for stochastic processes by Anne GÃ©gout-Petit and...
- Erratum: Do Restricted Driver's Licenses Lower Crash Risk Among Older Drivers? A Survival Analysis of Insurance Data From British Columbia. // Gerontologist;Dec2009, Vol. 49 Issue 6, p865
A correction to the article "Do Restricted Drivers Licenses Lower Crash Risk Among Older Drivers? A Survival Analysis of Insurance Data From British Columbia," by Glenyth Caragata Nasvadi and Andrew Wister, is presented.
- Assessing changes in the impact of cancer on population survival without considering cause of death. Brown, Barry W.; Brauner, Christopher // JNCI: Journal of the National Cancer Institute;01/01/97, Vol. 89 Issue 1, p58
Presents a study that assesses changes in the impact of cancer on population survival without considering cause of death in the United States. Increase in age- and incidence-adjusted 5-year survival; Increase in cancer incidence for three of four sex-race groups; Impact of the HIV-related...
- Charting the process of change: A primer on survival analysis. Luke, Douglas A. // American Journal of Community Psychology;Apr93, Vol. 21 Issue 2, p203
Provides a practical, nontechnical introduction to the use of survival analysis for social scientists. Discussion of important issues in using survival analysis; Illustration of common survival analysis tasks; Appendix of current survival analysis computer programs.
- Surviving sepsis bundle compliance: getting the time of the day it deserves. Borikar, Madhura; Tikotekar, Ashish; Parikh, Amay // Critical Care;
A letter to and response from the authors of the article "Differences in Compliance With Surviving Sepsis Campaign Recommendations According to Hospital Entrance Time: Day Versus Night" is presented.
- Survival Relative to Survival at Current pH. // CO2 Science;10/6/2015, Vol. 18, p1
A table is presented which provides information on the survival of benthic foraminifera (Ammonia aomoriensis) at a particular pH level during the experimental conditions, along with their journal references, after 42 days of exposure to elevated carbon dioxide (CO2).