Analysis of overlapping count data

Regression Analysis of Count Data

Three nonlinear count models, Poisson R.egression (PR), Negative Binomial Regression (NBR), and Generalized Poisson Regression (GPR) are used for assessing the effects of risk factors on agricultural injuries from farm injury data. A sample of 1,322 respondents who participated in the farm safety/injury baseline survey in nine rural counties in Alabama and Mississippi, aged 18 years and older a...

Mediation analysis for count and zero-inflated count data.

Different conventional and causal approaches have been proposed for mediation analysis to better understand the mechanism of a treatment. Count and zero-inflated count data occur in biomedicine, economics, and social sciences. This paper considers mediation analysis for count and zero-inflated count data under the potential outcome framework with nonlinear models. When there are post-treatment ...

Statistical Analysis of Spatial Count Data

Semiparametric analysis of zero-inflated count data.

Medical and public health research often involve the analysis of count data that exhibit a substantially large proportion of zeros, such as the number of heart attacks and the number of days of missed primary activities in a given period. A zero-inflated Poisson regression model, which hypothesizes a two-point heterogeneity in the population characterized by a binary random effect, is generally...

Regression analysis of multivariate panel count data.

We consider panel count data which are frequently obtained in prospective studies involving recurrent events that are only detected and recorded at periodic assessment times. The data take the form of counts of the cumulative number of events detected at each inspection time, along with explanatory covariates. Examples arise in diverse areas such as epidemiological studies, medical follow-up st...