Weighted hurdle regression method for joint modeling of cardiovascular events likelihood and rate in the US dialysis population.

ABSTRACT: We propose a new weighted hurdle regression method for modeling count data, with particular interest in modeling cardiovascular events in patients on dialysis. Cardiovascular disease remains one of the leading causes of hospitalization and death in this population. Our aim is to jointly model the relationship/association between covariates and (i) the probability of cardiovascular events, a binary process, and (ii) the rate of events once the realization is positive-when the 'hurdle' is crossed-using a zero-truncated Poisson distribution. When the observation period or follow-up time, from the start of dialysis, varies among individuals, the estimated probability of positive cardiovascular events during the study period will be biased. Furthermore, when the model contains covariates, then

SUBMITTER: Senturk D 

PROVIDER: S-EPMC4184989 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature