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In addition, [26] considers adopting a GARCH-type structure while modelling the correlations' dynamics.
In the first stage (labelled as model 2 in the remainder of the paper), information is borrowed across studies as well as across outcomes through modelling the correlations between effectiveness estimates on different outcomes.
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The approach of modelling the correlation as a hyperbolic function of a stochastic process has been recently proposed.
Several alternatives have been considered in modelling the correlation time of the ionospheric residuals, including the white noise model (WN), Gauss-Markov process, and the random walk model.
Through mixed effects modelling, the correlation structure of the data can be explicitly examined by researchers.
The use of multilevel models corrects this by modelling the correlation between the control sets.
The main contribution of this work is to model the correlations of the labels using a directed acyclic graph.
But correlation network methods can only be applied to model the correlations between numeric variables.
A spatial exponential covariance structure was used to model the correlations between repeated measurements.
We used an autoregressive structure to model the correlations between repeated measures over time.
Many studies have modeled the correlations of so-called processing speed measures with cognitive abilities such as spatial skill [3].
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