A goodness-of-fit test for the bivariate necessary-but-not-sufficient relationship

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dc.contributor.advisorde Leon, Alexander R.
dc.contributor.advisorKopciuk, Karen A.
dc.contributor.authorIlagan, Michael John
dc.contributor.committeememberNgamkham, Thuntida
dc.contributor.committeememberGodley, Jenny
dc.dateFall Convocation
dc.date.accessioned2022-11-15T17:43:16Z
dc.date.embargolift2022-07-31
dc.date.issued2020-07-31
dc.description.abstractIn the social sciences, theory often casts bivariate relationships between constructs in terms of logical asymmetries. For example, in psychology, one theory is that intelligence is necessary but not sufficient for creativity. But as average-based linear models fail to accommodate nuances of logical asymmetries, a mismatch between theory and method is common in the literature. Recent methodological work proposed the Linear Ceiling and Floor Probability Region (LCFPR) model, which analyzes bivariate relationships in terms of necessity and sufficiency. However, an erroneous treatment of nested models and a lack of a formal goodness-of-fit test remain unaddressed in the LCFPR framework. In this thesis, I propose a goodness-of-fit test for LCFPR that addresses such shortcomings. A simulation study shows that, using a nonparametric quantile, the power and size of the test are largely acceptable. Analyses of real datasets demonstrate the proposed procedure. Conclusions and future directions are outlined in the final chapter.
dc.identifier.citationIlagan, M. (2020). A goodness-of-fit test for the bivariate necessary-but-not-sufficient relationship (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.urihttp://hdl.handle.net/1880/115485
dc.identifier.urihttps://dx.doi.org/10.11575/PRISM/40452
dc.language.isoenen
dc.language.isoEnglish
dc.publisher.facultyGraduate Studiesen
dc.publisher.facultyScience
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en
dc.subjectlogical asymmetries
dc.subjectgoodness-of-fit
dc.subjectbeta distribution
dc.subjectintelligence
dc.subjectcreativity
dc.subject.classificationStatistics
dc.titleA goodness-of-fit test for the bivariate necessary-but-not-sufficient relationship
dc.typemaster thesis
thesis.degree.disciplineMathematics & Statistics
thesis.degree.grantorUniversity of Calgaryen
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
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