Statistical inference methods for recurrent event processes with shape and size parameters.

ABSTRACT: This paper proposes a unified framework to characterize the rate function of a recurrent event process through shape and size parameters. In contrast to the intensity function, which is the event occurrence rate conditional on the event history, the rate function is the occurrence rate unconditional on the event history, and thus it can be interpreted as a population-averaged count of events in unit time. In this paper, shape and size parameters are introduced and used to characterize the association between the rate function λ(·) and a random variable X. Measures of association between X and λ(·) are defined via shape- and size-based coefficients. Rate-independence of X and λ(·) is studied through tests of shape-independence and size-independence,

SUBMITTER: Wang MC 

PROVIDER: S-EPMC4581538 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature