Abstract
In a 1000 person random sample, the effects of time and territorial divisions on health scores were tested, both traditionally, and with the help of machine learning.
Traditional efficacy analysis consisted of
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confidence intervals,
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simple linear regressions.
Machine learning efficacy analysis consisted of complex-samples methods.
The machine learning methods provided better sensitivity of testing, and were more informative.
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Cleophas, T.J., Zwinderman, A.H. (2019). Complex-Samples for Efficacy Analysis. In: Efficacy Analysis in Clinical Trials an Update. Springer, Cham. https://doi.org/10.1007/978-3-030-19918-0_4
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DOI: https://doi.org/10.1007/978-3-030-19918-0_4
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19917-3
Online ISBN: 978-3-030-19918-0
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