Sentence examples for binomial regression was preferred from inspiring English sources

Negative binomial regression was preferred over Poisson regression wherever there was over-dispersion with the Poisson model (i.e. the variance in the mean number of heterozygous SNPs within MIs being substantially higher than the mean).

Initial exploration of the prediction sample data indicated the presence of possible overdispersion (variance (δ=1.37) exceeded mean (μ=0.4) count of cases), so negative binomial regression was preferred to Poisson regression since it explicitly models any overdispersion with an extra dispersion parameter.

Negative binomial regression is preferred over Poisson regression for modeling the count data because of the overdispersion that is common with actual research data [ 40, 77].

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 used to analyse the differences in GP visits between the two years.

Binomial regression is considered the most adequate choice.

Further, the likelihood ratio test comparing the corresponding negative binomial regression model with the Poisson model was marginally significant (P LRT  = 0.052), therefore the negative binomial model was preferred.