Sentence examples for binomial regression to estimate from inspiring English sources

This paper uses a negative binomial regression to estimate whether variations in Operation Lifesaver activity across states and from year-to-year in individual states are related to the number of collisions and fatalities at crossings.

We use a negative binomial regression to estimate our model, since our outcomes were counts and their distribution was more overdispersed than would be found in a Poisson distribution [21].

We used logistic binomial regression to estimate relative risks (RR) and control potential confounders.

We used negative binomial regression to estimate incidence rate ratios, adjusting for age, sex, and reporting period.

Therefore, we used negative binomial regression to estimate the association of cleaning protocol (manual vs PPX-UV) with final colony count, adjusting for baseline counts.

Number of falls per person-year will be analysed using negative binomial regression to estimate the difference in falls rates between the two groups.

We used log-binomial regression to estimate relative risk (RR) and 95% confidence interval (CI) of categorical outcomes (e.g. limping).

We used log-binomial regression to estimate risk ratios (RRs) with 95% confidence intervals (CIs) for associations between each of the intrauterine, early-life, and childhood exposures and fibroid diagnosis by 35 years of age.

We relied upon percent agreement and Cohen's kappa (k) to quantify the concordance in caregivers' responses and multivariate log-binomial regression to estimate the impact of OHL on OHBs.

We defined low cognitive function as a BPP score in the bottom quartile and used a log-binomial regression to estimate crude and adjusted prevalence ratios (PRs) for a BPP score in this quartile, according to age at first hospitalisation for OM [ 22].

We adopted the negative binomial (NB) regression to estimate these multivariate models.