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The cost of rural health continues to be high in the United States despite an overall improvement in national health insurance enrolment. Stakeholder's perception of adverse selection remains a paramount culprit in the challenges of rural insurance markets. Risk attitude has been revealed as an alternative for measuring this phenomenon, given the 2014 prohibition law on pre-existing conditions and a subsequent repeal in 2018 accompanied by extensive debate among congress. We examine the existence of adverse selection in rural insurance markets by comparing the effects of pre-existing or chronic health conditions and risk attitudes in a Principal-Agent model.
Pubmed ID: 31218435
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A clustering tool designed mainly for Metagenomics studies, which clusters 16S rRNA sequences into Operational Taxonomic Units (OTU). By using a Gaussian Mixture model, CROP can automatically determine the best clustering result for 16S rRNA sequences at different phylogenetic levels without setting a hard cutoff threshold as hierarchical clustering does. Yet, at the same time, it is able to manage large datasets and to overcome sequencing errors.
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