Abstract
Tables and graphs are often used in clinical research articles. This chapter especially considers these items and addresses the way to create Tables and the ways to interpret graphs and curves in oncologic clinical research. Tables must present complete and clear access to data, and Figures should work as an enabler resource to better reveal interesting points in the article. The main tools used to identify associations between exposure and outcomes in clinical research are univariate regression and multivariate regression; here we describe the use of these methods. However, despite being widely used in cancer research, these tools are not easily interpreted, are sometimes overused, and may be associated with hidden biases.
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Araújo, R.L.C., Riechelmann, R.P. (2018). Interpretation of Results from Tables, Graphs, and Regressions in Cancer Research. In: Araújo, R., Riechelmann, R. (eds) Methods and Biostatistics in Oncology. Springer, Cham. https://doi.org/10.1007/978-3-319-71324-3_6
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DOI: https://doi.org/10.1007/978-3-319-71324-3_6
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