Marquez and Wakefield Publish New Research on Innovative Methods for Harmonizing Child Mortality Data Across Disparate Geographic Levels
Posted: 2/22/2021 (CSDE Research)
CSDE Fellow Neal Marquez and CSDE Affiliate Jon Wakefield recently published “Harmonizing Child Mortality Data at Disparate Geographic Levels” in Statistical Methods in Medical Research. The authors present a new method for analyzing masked survey data, using an approach that is consistent with the data-generating process. In addition, they critique two previously proposed approaches to analyzing masked data and illustrate that they are fundamentally flawed methodologically. To validate their method, they compare their approach with previously formulated solutions in several realistic simulation environments in which the underlying structure of the risk field is known. They simulate samples from spatiotemporal fields in a way that mimics the sampling frame implemented in the most common health surveys in low- and middle-income countries, the Demographic and Health Surveys and Multiple Indicator Cluster Surveys. In simulations, the newly proposed approach outperforms previously proposed approaches in terms of minimizing error while increasing the precision of estimates. The approaches are subsequently compared using child mortality data from the Dominican Republic where their findings are reinforced. The ability to accurately increase precision of child mortality estimates, and health outcomes in general, by leveraging various types of data, improves our ability to implement precision public health initiatives and better understand the landscape of geographic health inequalities. To read the article, click here.