Abstract
As discussed in Chapter 2, many variables are naturally measured on a categorical rather than a continuous scale. This is true for outcome variables as well as exposure variables. In the last chapter, we focused our attention on the comparison of two or more means, usually representing the mean outcomes in two or more exposure groups. In such cases, exposure is categorical (e. g., medical vs surgical treatment for renovascular hypertension), and the outcome is continuous (e.g., post-treatment blood pressure). The conventional approaches to comparing the mean outcomes include t- and z-tests, analysis of variance, and various nonparametric tests.
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© 1988 Springer-Verlag Berlin Heidelberg
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Kramer, M.S. (1988). Statistical Inference for Categorical Variables. In: Clinical Epidemiology and Biostatistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-61372-2_14
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DOI: https://doi.org/10.1007/978-3-642-61372-2_14
Publisher Name: Springer, Berlin, Heidelberg
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