Stats
Conditional Frailty Models (January 20, 2006)
One of the people I am working with is interested in using gap time analysis with a
conditional frailty model. I was impressed with this request and asked her to send any
relevant references that she had. She gave me a pointer to the following PDF file:
Repeated
events survival models: the conditional frailty model [PDF]. Box-Steffensmeier
J. Accessed on 2006-01-20.
[Abstract] Repeated events processes are ubiquitous across a great range of
important health, medical, and public policy applications, but models for these
processes have serious limitations. Alternative estimators often produce different
inferences concerning treatment effects due to bias and inefficiency. We recommend a
robust strategy for the estimation of effects in medical treatments, social conditions,
individual behaviors, and public policy programs in repeated events survival models
under three common conditions: heterogeneity across individuals, dependence across the
number of events, and both heterogeneity and event dependence. We develop a new model
for repeated events processes that accurately accounts for the various conditions of
heterogeneity and event dependence by using a frailty term, stratification, and gap time
formulation of the risk set. We examine the performance of these models and others that
are commonly used in applied work using Monte Carlo simulations, and apply the findings
to data on chronic granulomatous disease and cystic fibrosis. Key Words: repeated events
survival models, heterogeneity, event dependence, frailty. psweb.sbs.ohio-state.edu/prism/conditional_frailty.pdf
Probing around a bit, I found out that this was a presentation on May 10, 2005 at the
Program in Statistics & Methodology, Department of Political Science, The Ohio State
University. Details about this talk and other talks in the series are at
The particular application being used in this seminar involved factors associated with the
onset of civil war. A paper discussing this particular application, and a data appendix are
at:
The both papers cites a very good book on survival analysis:
-
Modeling Survival Data. Extending the Cox Model. Therneau TM, Grambsch PM (2000) New
York NY: Springer-Verlag. ISBN: 0387987843.
[BookFinder4U link]
When I get more time, I want to document some of the features of the frailty model. It is
very useful for modeling events that can occur repeatedly, like infection and
re-hospitalization.
This webpage was written on 2007-11-15
and was last modified on
2008-07-08.
Category: Survival analysis
