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Estimation Algorithm for Mixture of Experts Recurrent Event Model

Brooks, Timesha U
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Abstract

This paper proposes a mixture of experts recurrent events model. This general model accommodates an unobservable frailty variable, intervention effect, influence of accumulating event occurrences, and covariate effects. A latent class variable is utilized to deal with a heterogeneous population and associated covariates. A homogeneous nonparametric baseline hazard and heterogeneous parametric covariate effects are assumed. Maximum likelihood principle is employed to obtain parameter estimates. Since the frailty variable and latent classes are unobserved, an estimation procedure is derived through the EM algorithm. A simulated data set is generated to illustrate the data structure of recurrent events for a heterogeneous population.

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Date
2011-06-22
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Research Projects
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Keywords
Recurrent events, Mixture of Experts, Accumulating Events, Frailty, Effective Age
Citation
Brooks, Timesha U. "Estimation Algorithm for Mixture of Experts Recurrent Event Model." 2011. Thesis, Georgia State University. https://doi.org/10.57709/2245401
Embargo Lift Date
2011-09-19
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