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Statistical Methods in Medicine and Technology

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Applied Statistics

Part of the book series: Springer Series in Statistics ((SSS))

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Abstract

The number of hours of sleep gained by means of a soporific (sleep-inducing preparation) will generally vary from person to person. With the help of statistics we would like to make a statement on the average gain in the number of hours of sleep. We must also test whether the gain in the duration of sleep is statistically significant. Analyses of this type require not only knowledge of statistical methods but also a thorough familiarity with the field of study, because to determine the unique effects of specified causes we must be able to sort out the more important factors contributing to the phenomenon examined. These factors can be of a psychological or physical nature. In our example confidence in the medication and in the physician, as well as the physician’s attitude, are factors in the first category; charges in the diet, and in the daily routine belong to the second. To eliminate two influences of the first type, neither the physician assessing the therapy result nor the patient must know whether a soporific or a placebo is administered. This type of study is called a double blind trial.

If in the analysis of survival times in medicine or technology some objects are still alive at the end of the study their exact survival times are incomplete. These are called censored observations or censored times. More on this and on the comparison of survival distributions—see also pages 206, 210 and 235—is provided in the book by Lee (1980) with computer programs for 5 two sample tests and a k sample test [Chapter 5 and Appendix B, with both Peto and Peto’s tests: logrank test and generalized Wilcoxon test].

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Sachs, L. (1984). Statistical Methods in Medicine and Technology. In: Applied Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-5246-7_5

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