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dc.contributor.advisorHartung, Thomas
dc.creatorMyint, Leslie K
dc.date.accessioned2018-10-03T02:07:12Z
dc.date.available2018-10-03T02:07:12Z
dc.date.created2018-05
dc.date.issued2018-04-04
dc.date.submittedMay 2018
dc.identifier.urihttp://jhir.library.jhu.edu/handle/1774.2/59184
dc.description.abstractWhen scientists use familiar data analysis methods out of comfort or convenience, disciplines can suffer in their scientific inferences if these methods are not appropriate for their ultimate goals. Older fields experience this when long-standing methods are used simply for their longevity. Newer fields experience this when scientists transfer methods from other areas without evaluating their performance in these new domains. This work represents a collection of methods and results that contribute to evidence-based analytical practice in three different domains: mass spectrometry-based metabolomics, massively parallel reporter assays, and data science training. In the first two domains, we present new methods that improve current practice for comparative (differential) analysis in those fields. Specifically these methods are shown to be statistically calibrated and powerful compared to existing alternatives. In the third domain, we present experimental results regarding the actions and perceptions in data analysis practice. These results have implications for data analysis training and education. Broadly, in these three domains, we provide tools and discuss findings that enable higher quality work in applied research.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherJohns Hopkins University
dc.subjectmetabolomics
dc.subjectmass spectrometry
dc.subjectmassively parallel reporter assays
dc.subjectevidence-based data analysis
dc.subjecthuman-data interaction
dc.titleEvidence-based methods in studies of biology and data analysis
dc.typeThesis
thesis.degree.disciplineBiostatistics
thesis.degree.grantorJohns Hopkins University
thesis.degree.grantorBloomberg School of Public Health
thesis.degree.levelDoctoral
thesis.degree.namePh.D.
dc.date.updated2018-10-03T02:07:13Z
dc.type.materialtext
thesis.degree.departmentBiostatistics
dc.contributor.committeeMemberHansen, Kasper D.
dc.contributor.committeeMemberLeek, Jeffrey T.
dc.contributor.committeeMemberGoff, Loyal
dc.contributor.committeeMemberJager, Leah R.
dc.publisher.countryUSA
dc.creator.orcid0000-0003-2478-0331


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