Sentence examples for binomial regression models was from inspiring English sources

The selection of Poisson or negative binomial regression models was based on the model fit, assessed using a Pearson chi-square test.

Negative binomial regression models were constructed to test associations between generic E. coli (MPN/100 mL) in water from farms and variables.

Negative binomial regression models were used to assess the effect of street and street network characteristics on total crashes, severe injury crashes, and fatal crashes.

Negative binomial regression models were used to assess the statistical significance of risk factors associated with the within-farm number of Campylobacter-positive flocks (the outcome).

Negative binomial regression models are used to test these at the 6-hour shift unit of analysis on street robberies in the Strathclyde region of Scotland.

To examine the association between race, ethnicity sex, insurance, age, and age group with CRS, univariable and multivariable log binomial regression models were used.

Negative Binomial regression models were fitted to the incident number of infections with an offset with the annual number of ICU stays.

The randomized quantile residuals of the finally selected model (Eq. 8.51 Duchon) using 1st order derivatives in the penalty and three other negative binomial regression models were compared and validated for spatial independency.

Multivariable negative binomial regression models were used to evaluate the relationship between respiratory illnesses and variables found significant on univariate analysis while adjusting for potential confounding.

The Negative binomial regression models were calculated using function 'nbreg'nbreg

Negative binomial regression models were therefore fitted in favour of Poisson regression models.