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dc.contributor.authorCooke, Stephanie Carrieann
dc.date.accessioned2014-03-04T20:35:24Z
dc.date.available2014-03-04T20:35:24Z
dc.date.issued2012-08
dc.identifier.othercooke_stephanie_c_201208_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/cooke_stephanie_c_201208_ms
dc.identifier.urihttp://hdl.handle.net/10724/28237
dc.description.abstractThe purpose of this study is to find an optimal experimental design for cancer biomarker reproducibility studies. A biomarker is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention (CCR Focus March 9, 2010). Vital signs, such as blood pressure, can also be considered biomarkers. Experiments that measure biomarkers can be costly and time consuming. In response to these factors, this study has identified and developed an algorithm that determines optimal allocation of samples for the most effective experimental results. This biomarker reproducibility study estimates the variance of laboratory measurements by using the intraclass correlation coefficient (ICC), which, unlike the F test, uses no hypothesis testing of population means. The ICC evaluates the amount of overall variance relative to between-subject variability (von Eye et al. 2005). This study focuses on finding the most cost-efficient design for cancer biomarker studies assessing reproducibility.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectcancer biomarker, experimental design, intraclass correlation coefficient (ICC)
dc.titleDesign of cost-fffective cancer biomarker reproducibility studies
dc.typeThesis
dc.description.degreeMS
dc.description.departmentStatistics
dc.description.majorStatistics
dc.description.advisorKevin Dobbins
dc.description.committeeKevin Dobbins
dc.description.committeeCheolwoo Park
dc.description.committeeWilliam P. McCormick


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