Introduce the biostatistics programme in UM
We develop a new regression analysis approach to evaluating associations of covariates with outcomes measured from networks. This development is motivated from a study of infant growth that collects outcomes of event related potentials (ERP, a type of neuroimaging) measured over electroencephalogram (EEG) electrodes on the scalp. We propose a new generalized method of moments (GMM) that incorporates both established and data-driven knowledge of network topology among nodes in the estimation and inference to achieve robustness and efficiency. The GMM approach is computationally fast and stable to handle the regression analysis of network data, and conceptually it is simple with desirable properties in both estimation and inference. Both simulation studies and real EEG data analysis will be presented for illustration.
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