Sentence examples for binomial regression is used from inspiring English sources
[ 23] Now, when Poisson or negative binomial regression is used, the logarithmic link function is applied so E[ y i ] = log(μ i ), and the modeled response variable is: log (μ i ) = log (α i δ ) = log (α i ) − log .
The logistic regression, a generalized linear model used for binomial regression, is used for prediction of the probability of occurrence of an event by fitting data to a logistic curve.
Negative binomial regression is used when the outcome to be analysed is a count (such as deaths during a calendar year) and the Poisson model assumption that the mean is equal to variance is not met, usually because the data present greater dispersion.
Multivariate binomial regression was used to model the probability of adverse outcomes with respect to the absolute number of antenatal visits, after controlling for potentially confounding factors.
Negative Binomial Regression was used to model the dependent variables as a function of nodal and place-based crime-generating and crime-attracting characteristics of stations.
Prevalence proportion difference, by binomial regression, was used to compare the association between injury prevalence proportion and gender, both among adults and children.
Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency.
Poisson regression and negative binomial regression are used to quantify the influence of possible contributory factors on the incidence of killed and severe injury (KSI) crashes and slight injury crashes, respectively, while possible interventions by traffic flow are controlled.
Data analysis was performed using Stata 8. Binomial regression was used to obtain risk differences between treatments and 95% confidence intervals.
First, negative binomial regression was used to compare differences in fall rates between the cohorts (stroke, control) when controlling for sex and age.
