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Modelling the variance may be a means of gaining insight into health inequalities and developing hypotheses regarding contexts [ 5].
This way of modelling the variance due to the SNP will be discussed in detail in Discussion.
Network meta-analysis is becoming increasingly popular and a variety of approaches to modelling the variance components have been proposed in this setting [ 34- 37].
A more general approach (without restricting the data into three groups, but modelling the variance as a function of the mean) should be straightforward to implement.
Therefore by modelling the variance of the effect of the SNP, we also model the variance directly due to the SNP, irrespective of its frequency.
While having 2 replicates for each time-point/fragment is not ideal for modelling the variance encountered in RNA-seq, our sample preparation of including multiple individuals (20 fragments in each library) does offer some variance stabilization through biological averaging.
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In particular, we modeled the variance for the above three mean equations using GARCH, APARCH, EGARCH, TGARCH, and IGARCH models.
However, a notable limit is that it does not model the variance associated to a BG value.
To model the variance of different mixture component (or n.comp), the same variance for all n.comps except 2 and 3 is used.
The compound symmetry was chosen as appropriate to model the variance structure of the random effects.
Using the BB can be more complicated than linear models, depending on the need to model the variance.
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