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The reason is that the different methods are effectively estimating the effect in different populations, with different distributions of covariates.
This numerical method is robust against effects of the underlying grid.
When this method is used, the effect of a covariate depends on the transition.
The second method is to estimate effects of influenza in four seasons respectively, using the conventional interaction model.
Angle order methods are less effected by non-randomness in a clumped population if the events are essentially random within each sector.
The mathematical form of our basic models using the random effect method is specified as under.
The poor performance of hybrid method is due to primary effect of gradient term in (14).
An important aspect of the proposed method is that no matrix effects were observed.
The final method is the percentage placebo effect.
An important assumption underlying this method is that costs and effects are constant over time.
The first method gives only qualitative results, while the second method is quantitative and dose-effect curves can be done.
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