Parameter estimation for correlated recurrent events under informative monitoring
When subjects are monitored for a recurrent event over a period of time, each individual behaves like an experimental unit within which measurements may be correlated. The subject-specific observation window (i.e. monitoring period) constitutes another factor controlling the accumulation of events and censoring. We develop a procedure for estimating survivor parameters in the presence of joint effect of correlation and informative monitoring; specifically, for studies in which the survival time for a subject is censored because of deterioration of their physical condition or due to the accumulation of their event occurrences. In this manuscript, we approach the survivor parameter estimation problem by a fully parametric baseline hazard model where the intensity functions of the inter-event time and the duration of the monitoring period are reconciled through the generalized Koziol-Green (KG) model (Koziol and Green (1976) ), and the within experimental unit correlation modeled through frailty. We outline the Expectation Maximization (EM) steps for estimating Weibull parameters with correlated recurrent event data under informative monitoring. We apply our method to a real life data.
A. Adekpedjou and K. D. Zamba, "Parameter estimation for correlated recurrent events under informative monitoring," Statistical Methodology, Elsevier, May 2011.
The definitive version is available at https://doi.org/10.1016/j.stamet.2010.12.001
Mathematics and Statistics
Missouri Research Board
Keywords and Phrases
correlated recurrence times; counting processes; frailty model; generalized koziol-green model; informative monitoring; weibull inter-event times
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