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The standard errors and the confidence intervals are estimated, by default, under a binomial assumption for each haplotype frequency estimate.
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We calculated 95% CIs for standardized prevalence rates using a normal approximation and Breslow-Day standard errors, after being modified to use a binomial assumption for the variance of the crude stratum-specific rates (9).
The animal-level variation was modelled under the binomial assumption, with the potential for overdispersion accounted for by fitting an extra-binomial parameter.
By the assumption, for each, we get.
Further, the proportional hazards assumption for each covariate was tested.
The 95% confidence interval and p-values resulted from the binomial test for each case are given in the table.
We have performed two-tailed binomial test for each pair of homoeologous genes differing in expression.
To accommodate this phenomenon we use a different binomial distribution for each position within the reads.
However, our method differs: instead of using longitudinal data in only one regression model, for which Poisson models are better suited [14, 40], we use many consecutive Negative Binomial models, one for each time snapshot of the network, thus avoiding violating the assumptions of the Poisson model, and controlling for daily rhythms at the same time [43].
Dendrogram information includes a breakdown of the categories present in the cluster, as well as the enrichment P-values, calculated using the Binomial proportion test, for each category in the selected cluster.
(II) contradicting the assumption that for each.
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