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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.
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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.
The cumulative binomial test was used to examine the likelihood that the occurrence of a particular event (loss of the same allele in the invasive carcinoma and an associated epithelial sample) occurs at a particular probability when observed in repeated trials.
Negative binomial regression was used in cases where data showed evidence of over dispersion by performing likelihood ratio tests of the scale parameter.
A binomial model was used for the probability of encountering terns, and a negative binomial was used for the number of terns if encountered.
The beta binomial model was used to account for over-dispersion.
Negative binomial distribution was used for curve fitting.
A binomial test was used to check this assumption.
A binomial distribution was used.
Exact binomial CIs were used.
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