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        <datestamp>2024-09-16</datestamp>
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          <dc:contributor>Regenwetter, Michel</dc:contributor>
          <dc:contributor>Koehn, Hans Friedrich</dc:contributor>
          <dc:date>2024-05</dc:date>
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          <dc:description>Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms</dc:description>
          <dc:description>The student, Meichai Chen, accepted the attached license on 2024-05-02 at 15:34.</dc:description>
          <dc:description>The student, Meichai Chen, submitted this Thesis for approval on 2024-05-02 at 15:49.</dc:description>
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          <dc:title>Order-constrained inference: a nuanced approach to hypothesis testing</dc:title>
          <dc:creator>Chen, Meichai</dc:creator>
          <dc:date>2024-05-03</dc:date>
          <dc:subject>Order-constrained Inference</dc:subject>
          <dc:subject>Nuanced Hypotheses</dc:subject>
          <dc:subject>Model Competition</dc:subject>
          <dc:description>Many statistical analyses performed in psychological studies add extraneous assumptions that are not part of the theory. These added assumptions could adversely influence the conclusions one derives from the analyses. Order-constrained inference allows researchers to avoid unnecessary assumptions, translate verbal predictions into direct testable hypotheses, and run model selection among competing theories. We reanalyzed data from two separate case studies to highlight how one can use order-constrained modeling to formulate more nuanced hypotheses and test these hypotheses jointly. To further leverage order-constrained inference, we compared the performance of competing theories using Bayesian model selection methods in the second case study. We observe that order-constrained inference not only provides us with a coarse view of all the hypotheses at the joint level, it also offers a fine-grained perspective of all the hypotheses at the item level that might otherwise stay hidden if we only assessed trends at the aggregate level.</dc:description>
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          <dc:rights>Copyright 2024 Meichai Chen</dc:rights>
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            <discipline>Psychology</discipline>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <department>Psychology</department>
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