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      Making sense of some odd ratios: A tutorial and improvements to present practices in reporting and visualizing quantities of interest for binary and count outcome models.

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          Abstract

          Generalized linear models (GLMs) such as logistic and Poisson regression are among the most common statistical methods for modeling binary and count outcomes. Though single-coefficient tests (odds ratios, incidence rate ratios) are the most common way to test predictor-outcome relations in these models, they provide limited information on the magnitude and nature of relations with outcomes. We assert that this is largely because they do not describe direct relations with quantities of interest (QoIs) such as probabilities and counts. Shifting focus to QoIs makes several critical nuances of GLMs more apparent.

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          Author and article information

          Journal
          Psychol Addict Behav
          Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors
          American Psychological Association (APA)
          1939-1501
          0893-164X
          May 2022
          : 36
          : 3
          Affiliations
          [1 ] Department of Psychology.
          [2 ] Department of Psychiatry.
          [3 ] Department of Statistics.
          Article
          NIHMS1649535 2021-40400-001
          10.1037/adb0000669
          8553813
          33914563
          0d065d29-b394-4354-a4b9-ebc32ab8c1fd
          History

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