Sentence examples for binomial regression was introduced from inspiring English sources
Therefore, negative binomial regression was introduced to model the count data with overdispersion (that is, the variance is greater then the mean) [ 16, 17].
Log binomial regression was used to calculate adjusted PRs.
A negative binomial regression was used due to over dispersion.
Negative binomial regression was used instead of Poisson regression to account for overdispersion in the data.
Negative binomial regression was used instead of Poisson regression because of the over-dispersed data.
Negative binomial regression would be chosen if the p-value of the Vuong test was not significant (p > 0.05) indicating the zero-inflated negative binomial regression was not significantly better than the negative binomial regression.
Negative binomial regression was chosen because some count data were overdispersed (Kim and Kriebel, 2009).
Negative binomial regression was used to analyse the differences in GP visits between the two years.
Binomial regression is considered the most adequate choice.
The three analytical steps of the estimation procedure using negative binomial regressions are explained below.
As the first step in the analysis, negative binomial regressions are performed for each dependent variable.
