Regression Analysis of Panel Count Data II

  • Jianguo Sun
  • Xingqiu Zhao
Chapter
Part of the Statistics for Biology and Health book series (SBH, volume 80)

Abstract

This chapter discusses the same problem as in the previous chapter, but under different situations. A basic assumption behind the methods described in the last chapter is that the underlying recurrent event process of interest and the observation process are independent of each other conditional on covariates. As pointed out before, sometimes this assumption may not hold. In other words, the observation process may depend on or contain relevant information about the recurrent event process. In a study on the occurrence of asthma attacks, for example, the observations on or clinical visits of asthma patients may be related to or driven by the numbers of the asthma attacks before the visits. The same can occur for similar recurrent event studies such as these on some disease infections or tumor development. In these situations, it is clear that the methods given in Chap. 5 are not valid as they would lead to biased estimation or wrong conclusions. The data arising from these cases are often referred to as panel count data with informative or dependent observation processes.

Keywords

Placebo Filtration Covariance Thiotepa 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Jianguo Sun
    • 1
  • Xingqiu Zhao
    • 2
  1. 1.Department of StatisticsUniversity of MissouriColumbiaUSA
  2. 2.Department of Applied MathematicsThe Hong Kong Polytechnic UniversityHong KongHong Kong SAR

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