Some Statistical Methods to Differentiate a Treatment Effect for Small Shifts in the Tail of a Distribution
| Autor: | Michael Stepanavage, Minzhi Liu, Mei X. Wu, Aditi Shahane |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Public Health
Environmental and Occupational Health Contrast (statistics) Pharmacology (nursing) Variable (computer science) Distribution (mathematics) Drug Guides Statistics Econometrics Standard test Pharmacology (medical) Statistical analysis Treatment effect Mathematics Event (probability theory) |
| Zdroj: | Drug Information Journal. 35:1235-1246 |
| ISSN: | 2164-9200 0092-8615 |
| DOI: | 10.1177/009286150103500420 |
| Popis: | The intervention of most clinical therapies typically involves shifting the central tendency of a response variable. There are many analytical methods to summarize these shifts and provide inferential results for treatment differences. Differences between treatments, however, cannot always be discerned by central tendency shifts. Rare individual events of extreme deviations from the central tendency cannot be easily captured by standard test statistics and summary results. Instead, these extreme rare event instances need to be summarized by analytical methods to describe and test shifts between treatments that only occur in a small proportion of patients. In fact, in the case of extreme data, the achievement of significance based upon central tendency summaries may not be clinically meaningful. This paper will compare and contrast some well and lesser known analytical methods to differentiate a treatment effect for small shifts in the tail of a distribution. In particular, the following statistical method... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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