Postdoctoral Fellowship Proposal

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I am M. Patricia Cifuentes, a postdoctoral researcher at Ohio State University, appointed by the College of Public Health and Biomedical Informatics. I am an MD specialized in statistics with a doctoral degree on Public Health.
I contact you to share some research ideas I propose in the context of my application to the Yerby postdoctoral fellowship program for which I suggested you as faculty mentors.
The proposal I presented consists on developing theory-based and data-driven models of health complexity for contributing to the health theoretical development, providing coherence and context to fragmented evidence of health practice, and bringing closer health theory and facts. I briefly described this proposal in my application according to supplemental questions made by the program.
The proposal is framed by formulations of health theories which assemble the health´s body of knowledge. Therefore, Ecosocial theory formulated by Dr. Krieger is a keystone as it addresses diverse issues of health complexity. As the development of scientific theories relies on
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There are several methods available to reconstruct networks from this widely available data format. My emphasis on the method of Bayesian networks (BN) has relied on their non-pairwise mechanism of inference that introduces effects of “third variables” as a way to control confounding. The vast use and development of BN provides multiple tools to model diverse complexity issues, such as their approaches to causality.
Two types of interdependent network models are proposed: factor based and agent based networks. The networks obtained can be navigated at the local level by each pairwise link or by groups of linked nodes. However, the complexity of these models needs to be explored by network analysis methods to find general patterns of emergent

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