Abstract:
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This paper discusses regression analysis of panel count data with dependent observation and dropout processes. For the problem, a general mean model is presented that can allow both additive and multiplicative effects of covariates on the underlying point process. In particular, the proportional rates model and the accelerated failure time model are employed to describe covariate effects on the observation and dropout processes, respectively. For estimation of regression parameters, some estimating equation-based procedures are developed and asymptotic properties of the proposed estimates are established. In addition, a resampling approach is proposed for estimating covariance matrix of the proposed estimates and a model checking procedure is provided. Results from an extensive simulation study indicate that the proposed methodology works well for practical situations and it is applied to a motivating set of real data.
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