Yu G, Li Y, Zhu L, Zhao H, Sun J, Robison LL. An Additive-Multiplicative Mean Model for Panel Count Data with Dependent Observation and Dropout Processes.
Scand Stat Theory Appl 2019;
46:414-431. [PMID:
31223184 PMCID:
PMC6586419 DOI:
10.1111/sjos.12357]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 08/31/2018] [Indexed: 11/30/2022]
Abstract
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 addition, the proportional rates model and the accelerated failure time model are employed to describe possible covariate effects on the observation process and the dropout or follow-up process, respectively. For estimation of regression parameters, some estimating equation-based procedures are developed and the asymptotic properties of the proposed estimators are established. In addition, a resampling approach is proposed for estimating covariance matrix of the proposed estimator and a model checking procedure is also 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.
Collapse