Sentence examples for binomial regression models have from inspiring English sources

Various negative binomial regression models have been developed to study Lyme disease in connection to climate and/or landscape factors.

In comparison to regular Poisson regression models, negative binomial regression models have an extra parameter to model the overdispersion.

Statistical models, such as Poisson or negative binomial regression models, have been employed to analyze vehicle accident frequency for many years.

For example, multiple linear regression, Poisson regression, and negative binomial regression models have been used to identify the relationship among accidents and contributing factors (e.g. data on mobility or on involved users).

Negative binomial regression models have been shown to employ a more robust method to fit count data in the presence of overdispersion than the Poisson regression model itself.

As a result, the zero-inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) regression models have received considerable attention when used in ANC service visits pregnant women's studies.

Zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) dual-state regression models have been widely applied in the social, economic, political and epidemiological sciences, although caution is warranted when the strong assumption of zeros arising from two processes cannot be sustained theoretically [ 18, 19].

Negative Binomial and Poisson Inverse Gaussian regression models have also been proposed as overdispersed alternatives to the Poisson regression model (e.g. Lawless [1987]; Dean et al. [1989]; Xue and Deddens [1992]).

Cox regression models have shown PR similar to those of using Log-binomial regression models [ 25, 26].

Regression analysis (such as linear regression models, negative binomial regression models and Poisson regression models) has been the most popular technique in crash analysis because the connection between accidents and factors affecting them can be evidently identified.

Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent.