A new paradigm for hypothesis testing in medicine, with examination of the Neyman Pearson condition

Abstract
In the past, hypothesis testing in medicine has employed the paradigm of the repeatable experiment. In statistical hypothesis testing, an unbiased sample is drawn from a larger source population, and a calculated statistic is compared to a preassigned critical region, on the assumption that the comparison could be repeated an indefinite number of times. However, repeated experiments often cannot be performed on human beings, due to ethical or economic constraints. We describe a new paradigm for hypothesis testing which uses only rearrangements of data present within the observed data set. The token swap test, based on this new paradigm, is applied to three data sets from cardiovascular pathology, and computational experiments suggest that the token swap test satisfies the Neyman Pearson condition.
Keywords No keywords specified (fix it)
Categories (categorize this paper)
Options
 Save to my reading list
Follow the author(s)
My bibliography
Export citation
Find it on Scholar
Edit this record
Mark as duplicate
Revision history Request removal from index
 
Download options
PhilPapers Archive


Upload a copy of this paper     Check publisher's policy on self-archival     Papers currently archived: 11,793
External links
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library
References found in this work BETA

No references found.

Citations of this work BETA

No citations found.

Similar books and articles
Analytics

Monthly downloads

Added to index

2009-01-28

Total downloads

7 ( #191,580 of 1,099,716 )

Recent downloads (6 months)

2 ( #186,613 of 1,099,716 )

How can I increase my downloads?

My notes
Sign in to use this feature


Discussion
Start a new thread
Order:
There  are no threads in this forum
Nothing in this forum yet.