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The animal-level variation was modelled under the binomial assumption, with the potential for overdispersion accounted for by fitting an extra-binomial parameter.
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All models will be corrected for possible overdispersion, either by using an adjustment parameter in the Poisson model or by fitting a negative binomial regression model.
If it is assumed that that all infectious mosquitoes are equally infectious, this can be estimated by fitting a chain binomial model (33).
We obtained sex-specific and age-group specific MN meage-group specificfitting a negative binoMNal randomeanfrequencies to the MN count of each subyect (Lindsey 1995).
We assume that an individual receives n bites, where the size of each sporozoite inoculum, Si (such that the total initial inoculum S0 = Σ Si), is sampled from a negative binomial distribution obtained by fitting a negative binomial model to counts of parasites inoculated per-bite by anopheline mosquitoes.
Differential expression was evaluated by fitting a negative binomial generalized linear model for each feature and then adjusting the P-value for multiple testing using the Benjamini-Hochberg correction [ 78] with a false discovery rate (FDR) of 0.05.
We mapped ASE by fitting a binomial distribution per SNP using maximum likelihood estimation and then assessed significance by using a likelihood ratio test.
For these reasons, we ultimately took a Bayesian approach by fitting a multivariate negative binomial reduced rank random regression model using a Metropolis Hastings algorithm implemented in R [ 17].
Here, we applied an extra-binomial model proposed by Williams (1982) to our data.
We propose to use and extend such an extra-binomial model originally described by Williams (1982).
One can estimate the LOR of a test and its CI more accurately by some extra computations, or by fitting a slightly modified model.
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