Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, d...

This paper represents the comparison between Negative Binomial Regression model and Generalized Poisson Regression model for over-dispersion count data. For this comparison, we used BDHS 2007 data in where the response variable is the total children ever born which is a count data. When the response variable is count, then Poisson Regression Model as a Generalized Linear Model is widely and pop...

In the remainder, we call such a variety a convex symplectic variety. A convex symplectic variety has been studied in [K-V], [Ka 1] and [G-K]. One of main difficulties we meet is the fact that tangent objects TX and T 1 Y are not finite dimensional, since Y may possibly have non-isolated singularities; hence the usual deformation theory does not work well. Instead, in [K-V], [G-K], they introdu...

BACKGROUND Poisson regression is routinely used for analysis of epidemiological data from studies of large occupational cohorts. It is typically implemented as a grouped method of data analysis in which all exposure and covariate information is categorised and person-time and events are tabulated. AIMS To describe an alternative approach to Poisson regression analysis using single units of pe...

We propose a novel alternative to case-control sampling for the estimation of individual-level risk in spatial epidemiology. Our approach uses weighted estimating equations to estimate regression parameters in the intensity function of an inhomogeneous spatial point process, when information on risk-factors is available at the individual level for cases, but only at a spatially aggregated level...

A class of n-ary Poisson structures of constant rank is indicated. Then, one proves that the ternary Poisson brackets are exactly those which are defined by a decomposable 3-vector field. The key point is the proof of a lemma which tells that an n-vector (n ≥ 3) is decomposable iff all its contractions with up to n− 2 covectors are decomposable. In the last years, several authors have studied g...

A class of n-ary Poisson structures of constant rank is indicated. Then, one proves that the ternary Poisson brackets are exactly those which are defined by a decomposable 3-vector field. The key point is the proof of a lemma which tells that an n-vector (n ≥ 3) is decomposable iff all its contractions with up to n − 2 covectors are decomposable. In the last years, several authors have studied ...

In crash frequency studies, correlated multivariate data are often obtained for each roadway entity longitudinally. The multivariate models would be a potential useful method for analysis, since they can account for the correlation among the specific crash types. However, one issue that arises with this correlated multivariate data is the number of zero counts increases as crash counts have man...

A smooth manifold M is endowed by a Poisson pair if two linearly independent bivectors c1, c2 are defined on M and moreover cλ = λ1c1+ λ2c2 is a Poisson bivector for any λ = (λ1, λ2) ∈ R 2. A bihamiltonian structure J = {cλ} is the whole 2-dimensional family of bivectors. The structure J (the pair (c1, c2)) is degenerate if rank cλ < dim M,λ ∈ R 2. The degenerate bihamiltonian structures play i...

BACKGROUND Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies ...