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A Zero-Inflated Negative Binomial model is used to explore the factors affecting the initial adoption and the increase of organic food in PSFP at the regional level.
When a negative binomial model is used, the dispersion has to be estimated before a differentially expressed gene (DEG) analysis is carried out.
In the presence of negative control data, a binomial model is used to determine whether the read enrichment relative to the control is significant.
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The beta binomial model was used to account for over-dispersion.
A binomial model was used for the probability of encountering terns, and a negative binomial was used for the number of terns if encountered.
In particular, random parameter negative binomial model was used to investigate pedestrian crashes.
A zero-inflated negative binomial model was used as the estimation method.
A negative binomial model was used to compute the measured trough concentrations.
A negative binomial model was used to compute the KDIGO class at day 90.
The binomial model was used to estimate the confidence interval (CI).
A binomial model was used with complementary log-log link and the interval length as offset variable [ 23].
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