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October 19, 2025Seminars in Cardiothoracic and Vascular Anesthesia1 citations

Statistics for the Clinician I: Categorical Variables

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RMR. Baños MadridJBJordan A ButtnerMSMark Shilling

Key Points

  • Categorical variables are essential for understanding associations in clinical data, enhancing research outcomes.
  • The chi-square and Fisher’s exact tests are popular methods for analyzing categorical data, helping to reveal significant relationships.
  • Effect sizes such as relative risk and odds ratio are crucial for interpreting outcomes of categorical analyses in research.
  • Understanding these statistical methods can refine clinicians' engagement with literature and improve their research capabilities.

Abstract

Categorical variables are an integral part of clinical research. This article introduces their uses and most common analyses for clinicians seeking additional statistics exposure to more critically engage with literature and refine their own research endeavors. We describe and demonstrate the two most common tests of association for categorical variables: chi-square and Fisher’s exact tests, along with their underlying logic, result interpretations, and relative strengths and weaknesses. We also introduce and explain two of the most common measurements of effect size in analyses of categorical outcomes: relative risk (RR) and odds ratio (OR).

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Cite This Study

Madrid et al. (2025) studied this question.

synapsesocial.com/papers/68f43eeb854d1061a58aba94https://doi.org/10.1177/10892532251389293
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