Abstract
This chapter discusses statistical analysis of multivariate panel count data, which arise when there exist several related types of recurrent events and study subjects are observed only at discrete time points. As remarked before, in this case, an issue that does not exist for univariate panel count data is the correlation between different types of events. To deal with it, two approaches are commonly used as with multivariate failure time data (Hougaard, 2000). One is the marginal model approach that leaves the correlation arbitrary, and the other is the joint model approach that characterizes the correlation through the use of some latent or random variables. In this chapter, we mainly adopt the marginal model approach and consider two problems, nonparametric comparison of treatments in terms of mean functions and regression analysis.
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Sun, J., Zhao, X. (2013). Analysis of Multivariate Panel Count Data. In: Statistical Analysis of Panel Count Data. Statistics for Biology and Health, vol 80. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8715-9_7
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DOI: https://doi.org/10.1007/978-1-4614-8715-9_7
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