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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 269-282 |
| Number of pages | 14 |
| Journal | Theoretical Medicine |
| Volume | 7 |
| Issue number | 3 |
| DOIs | |
| State | Published - Oct 1986 |
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Keywords
- Computer simulation
- Hypothesis test
- Neyman Pearson lemma
- Token swap test
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health
- Medicine (miscellaneous)
Cite this
A new paradigm for hypothesis testing in medicine, with examination of the Neyman Pearson condition. / Moore, G. William; Hutchins, Grover M.; Miller, Robert E.
In: Theoretical Medicine, Vol. 7, No. 3, 10.1986, p. 269-282.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A new paradigm for hypothesis testing in medicine, with examination of the Neyman Pearson condition
AU - Moore, G. William
AU - Hutchins, Grover M.
AU - Miller, Robert E
PY - 1986/10
Y1 - 1986/10
N2 - 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.
AB - 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.
KW - Computer simulation
KW - Hypothesis test
KW - Neyman Pearson lemma
KW - Token swap test
UR - http://www.scopus.com/inward/record.url?scp=0022798442&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0022798442&partnerID=8YFLogxK
U2 - 10.1007/BF00539848
DO - 10.1007/BF00539848
M3 - Article
C2 - 3798393
AN - SCOPUS:0022798442
VL - 7
SP - 269
EP - 282
JO - Theoretical Medicine and Bioethics
JF - Theoretical Medicine and Bioethics
SN - 1386-7415
IS - 3
ER -