Flexible parametric illness-death models
Sally R. Hinchliffe
Department of Health Sciences
University of Leicester
Leicester, UK
[email protected]
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David A. Scott
Oxford Outcomes Ltd
Oxford, UK
[email protected]
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Paul C. Lambert
Department of Health Sciences
University of Leicester
Leicester, UK
and
Department of Medical Epidemiology and Biostatistics
Karolinska Institutet
Stockholm, Sweden
[email protected]
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Abstract. It is usual in time-to-event data to have more than one event of
interest, for example, time to death from different causes. Competing risks models
can be applied in these situations where events are considered mutually exclusive
absorbing states. That is, we have some initial state—for example, alive with
a diagnosis of cancer—and we are interested in several different endpoints, all
of which are final. However, the progression of disease will usually consist of
one or more intermediary events that may alter the progression to an endpoint.
These events are neither initial states nor absorbing states. Here we consider
one of the simplest multistate models, the illness-death model. stpm2illd is a
postestimation command used after fitting a flexible parametric survival model
with stpm2 to estimate the probability of being in each of four states as a function
of time. There is also the option to generate confidence intervals and transition
hazard functions. The new command is illustrated through a simple example.
View all articles by these authors:
Sally R. Hinchliffe, David A. Scott, Paul C. Lambert
View all articles with these keywords:
illdprep, stpm2illd, survival analysis, multistate models, flexible parametric models
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