Abstract
With continuous outcome data (Chap. 1), the standard deviation is generally used to estimate the spread in a data sample. The standard deviation is, then, used for multiple purposes like null-hypothesis testing and the computation of confidence intervals. With binary outcome data things are different. Instead of a mean value the number of responders is calculated as a “kind of” mean value. In a data sample with binary outcome (yes-no outcome), the spread is estimated with the equation, √(p(1−p), where p = the proportion of responders, otherwise called the (yes-data fraction versus all data). This chapter assesses how these estimators can be used in practice for testing null-hypotheses and confidence intervals of binary outcome data.
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© 2016 Springer International Publishing Switzerland
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Cleophas, T.J., Zwinderman, A.H. (2016). Data Spread: Standard Deviations, One Sample Z-Test, One Sample Binomial Test. In: Clinical Data Analysis on a Pocket Calculator. Springer, Cham. https://doi.org/10.1007/978-3-319-27104-0_35
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DOI: https://doi.org/10.1007/978-3-319-27104-0_35
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27103-3
Online ISBN: 978-3-319-27104-0
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