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The hurdle negative binomial model was implemented using MATLAB's GPstuff toolbox [ 29].

The model was implemented in WinBUGS [18].

The generalized linear model was implemented to determine the best model fit for recognition rates using the glmer function from the lme4 package with binomial error structure and logit link function (GLMM; Baayen, Davidson, & Bates, 2008).

The model is implemented using NetLogo software.

Two independent DTI models were implemented.

Two pairs of sites models were implemented.

Two commonly used error models were implemented.

In particular, random parameter negative binomial model was used to investigate pedestrian crashes.

By Vuong test, zero-inflated negative binomial regression model was not significantly better than negative binomial model (z = 1.14, p = 0.128), thus negative binomial model was chosen.

The generalized linear mixed model (binomial family function) was implemented to determine the best model fit for recognition rates using the glmer function from the lme4 package.

It is precisely because the binomial model is unable to fit overdispersed binomial data that the application of the beta-binomial is necessary.