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We did Bayesian network meta-analyses using a binomial likelihood model.
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The effect of sample date, host sex and host age on the likelihood of Bd infection was investigated using a binomial model.
Health workers' self-reported likelihood of leaving their jobs was modelled using a binomial logistic regression model, with the variable dichotomized into not at all or not very likely vs. fairly or very likely.
Survival was modeled using a binomial error distribution.
Using a binomial effect size display for the link between engagement and subsequent customer satisfaction the findings were r =.43.
An example is provided in Chu et al.[ 53] where parameterization of the within-study model enabled the special case of diagnostic sensitivity and specificity to be jointly modelled with disease prevalence using a trivariate binomial likelihood.
A binomial likelihood is used to incorporate the number of subjects experiencing an event (half the number of patients) and the number of patients analysed in to the model: (19) Note that r s,k should be calculated outside the model to ensure it is a whole number.
A binomial likelihood distribution was used for the incident number of deaths for every two month interval, which was calculated based on the survival percentages from the Kaplan-Meier curves and the number of patients at risk at the beginning of the interval in each arm of each study, assuming a constant hazard rate within each interval (see Jansen and Cope [ 16] for more details).
Studies reporting the number of participants healed (AD) are used to inform a probability parameter, and a Binomial likelihood was defined for this subset of the evidence-set.
A binomial likelihood model 7 which accounts for use of multi-arm trials was used for analyses, given outcomes were dichotomous and included multi-arm trials.
And we said we're going to make this a binomial likelihood.
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