Abstract
This chapter describes the difficulty of interpreting clinical trial results when the prospective analysis plan of that trial has been altered. After providing four examples of problematic trial results that had their findings reversed, the necessity of a fixed research protocol is derived from key principles. Investigators generally wish to extend the results from their research sample to the larger population; however, this delicate extension is complicated by the presence of sampling error. No computational or statistical tools can remove sampling error—the best that researchers can do is to provide the medical and regulatory communities with a measure of the distorting effect that sampling error produces. Researchers accomplish this by providing an estimate of how likely it is that the population produced a misleading sample for them to study. However, these estimators are easily damaged and, when damaged, provide misleading assessments. The tools and techniques developed in this chapter to avoid untrustworthy estimation will be the basis of our subsequent work on interpretation of multiple analyses in clinical trials.
Dr. Anita Deswal and instrumental in describing the results of several of the clinical trials that are discussed in this chapter.
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(2003). Multiple Analyses and the Random Experiment. In: Multiple Analyses in Clinical Trials. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/0-387-21813-0_3
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DOI: https://doi.org/10.1007/0-387-21813-0_3
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