Analyzing clustered count data with a cluster specific random effect zero-inflated Conway-Maxwell-Poisson distribution.

ABSTRACT: In recent years, data analysis techniques have been developed in biological and medical research areas with different types of count distributions. In particular, zero-inflated versions of parametric count distributions have been used to model excessive zeros that are often present in these assays. Perhaps, the most common count distribution which has been used for analyzing such data is the Poisson distribution. However, a Poisson distribution, having a single underlying parameter, cannot cope with any other data dispersion pattern besides equidispersion. A negative binomial distribution is capable of modeling overdispersed, but not underdispersed data. However, a Conway-Maxwell-Poisson (CMP) distribution (Conway, R. W., and Maxwell, W. L., 1962) can handle not only overdispersion but als

SUBMITTER: Choo-Wosoba H 

PROVIDER: S-EPMC6510495 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature