Journal article

Evaluating the impact of Hazelwood mine fire event on students’ educational development with Bayesian interrupted time-series hierarchical meta-regression

Caroline X Gao, Jonathan C Broder, Sam Brilleman, Emily Berger, Jillian Ikin, Catherine L Smith, Tim CH Campbell, Rory Wolfe, Fay Johnston, Yuming Guo, Matthew Carroll

Cold Spring Harbor Laboratory

Abstract

AbstractBackgroundDisasters and other community-wide events can introduce significant interruptions and trauma to impacted communities. Children and young people can be disproportionately affected with additional educational disruptions. With the increasing threat of climate change, establishing a timely and adaptable framework to evaluate the impact of disasters on academic achievement is needed. However, analytical challenges are posed by the availability issue of individual-level data.MethodsA new method, Bayesian hierarchical meta-regression, was developed to evaluate the impact of the 2014 Hazelwood mine fire (a six-week fire event in Australia) using only aggregated school-level data f..

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University of Melbourne Researchers