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Application of Finite Mixture Models for Vehicle Crash Data Analysis

Lord, Dominique (contributor) - 2010

Developing sound or reliable statistical models for analyzing vehicle crashes is veryimportant in highway safety studies. A difficulty arises when crash data exhibit overdispersion.Over-dispersion caused by unobserved heterogeneity is a serious problemand has been addressed in a variety ways...

Persistent link: https://www.econbiz.de/10009464902

Spline-based sieve semiparametric generalized estimating equation for panel count data

Hua, Lei - 2010

In this thesis, we propose to analyze panel count data using a spline-basedsieve generalized estimating equation method with a semiparametric proportional mean model E(N(t)|Z) = Λ0(t) eβT0Z. The natural log of the baseline mean function, logΛ0(t), is approximated by a monotone cubic B-spline...

Persistent link: https://www.econbiz.de/10009466051

On the nature of over-dispersion in motor vehicle crash prediction models

Mitra, Sudeshna; Washington, Simon - 2007

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts?variation over and above that accounted for by the Poisson density. The extra-variation ? or dispersion ? is...

Persistent link: https://www.econbiz.de/10009483403

Residual Diagnostic Methods for Bayesian Structural Equation Models

Stokes-Riner, Abbie; Thurston, Sally W.

model assumptions. Individual-level residuals are easy to estimate in the Bayesian SEM and are used to dene posterior … predictive checks for model assumptions. The empirical cumulative distribution function of the residuals is used to test the … assumption that the residual error is normally distributed. Cumulative sums of the residuals are used to check the assumption …

Persistent link: https://www.econbiz.de/10009483015