Event History Analysis in Continuous Time
Publikation: Bidrag til bog/antologi/rapport › Encyclopædiartikel › Forskning › fagfællebedømt
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Event History Analysis in Continuous Time. / Andersen, Per K.; Keiding, Niels.
International Encyclopedia of the Social & Behavioral Sciences. red. / James D. Wright. 2. udg. Elsevier Science Inc., 2015. s. 310-319.Publikation: Bidrag til bog/antologi/rapport › Encyclopædiartikel › Forskning › fagfællebedømt
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TY - ENCYC
T1 - Event History Analysis in Continuous Time
AU - Andersen, Per K.
AU - Keiding, Niels
PY - 2015
Y1 - 2015
N2 - Event history data are obtained by observing individuals over time, focusing on times of occurrence of certain events and the types of event occurring. A review is given of event history analysis (in continuous time) based on multistate models. Examples of such models include the two-state model for survival data and the competing risks and disability models. The likelihood function for a multistate model is presented using the theory of counting processes with special emphasis on models with piecewise constant transition intensities, nonparametric models, and models for the transition intensities including covariates along the lines of the semiparametric Cox proportional hazards regression model for survival data. Direct models for various marginal features of event history data, such as state occupation probabilities, are also discussed. Finally, the influence of observational patterns on the inference is discussed.
AB - Event history data are obtained by observing individuals over time, focusing on times of occurrence of certain events and the types of event occurring. A review is given of event history analysis (in continuous time) based on multistate models. Examples of such models include the two-state model for survival data and the competing risks and disability models. The likelihood function for a multistate model is presented using the theory of counting processes with special emphasis on models with piecewise constant transition intensities, nonparametric models, and models for the transition intensities including covariates along the lines of the semiparametric Cox proportional hazards regression model for survival data. Direct models for various marginal features of event history data, such as state occupation probabilities, are also discussed. Finally, the influence of observational patterns on the inference is discussed.
KW - Censored data
KW - Competing risks
KW - Counting process
KW - Cox regression model
KW - Event history analysis
KW - Markov process
KW - Multistate model
KW - Piecewise constant intensities
KW - State occupation probability
KW - Survival analysis
KW - Time-dependent covariate
KW - Transition intensity
KW - Transition probability
U2 - 10.1016/B978-0-08-097086-8.31131-X
DO - 10.1016/B978-0-08-097086-8.31131-X
M3 - Encyclopedia chapter
AN - SCOPUS:85043432443
SN - 9780080970868
SP - 310
EP - 319
BT - International Encyclopedia of the Social & Behavioral Sciences
A2 - Wright, James D.
PB - Elsevier Science Inc.
ER -
ID: 201449092