The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation....

This paper explores differences in the frequency with which students from different schools reach high levels of math achievement. Data from the American Mathematics Competitions is used to produce counts of high-scoring students from more than two thousand public, coeducational, non-magnet,...

This paper explores differences in the frequency with which students from different schools reach high levels of math achievement. Data from the American Mathematics Competitions is used to produce counts of high-scoring students from more than two thousand public, coeducational, non-magnet,...

This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a new zero-inflated count data model that is based on two homogeneous Poisson processes and accounts for exposure time in a theory consistent way. The new model is used in an...

The widespread popularity and use of both the Poisson and negative binomial models for count data arises, in part, from their derivation as the number of arrivals in a given time period assuming exponenitally distributed interarrival times (without and with heterogeneity in the underlying base...