Copositive matrices and Simpson's paradox
β Scribed by Petros Hadjicostas
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 512 KB
- Volume
- 264
- Category
- Article
- ISSN
- 0024-3795
No coin nor oath required. For personal study only.
β¦ Synopsis
Given a finite population characterized by two attributes A and B, and a factor C with n levels, one case of Simpson's paradox (SP) occurs when A and B are positively associated within each level of C, but they are negatively associated or independent in the population. Given an attribute K, let K be its complement. Assume the conditional proportions of the combinations of attributes AB, AB, AB, A B, respectively, within each level of C are known to the analyst, but the proportions of the n subpopulations (corresponding to the n levels of C) in the population are not known to the analyst. The problem is to find conditions under which SP occurs, and find the probability of SP. The first part of the problem is solved completely for all n >/2 using properties of copositive matrices, and the theorems of . The second part of the problem is solved partially.
π SIMILAR VOLUMES
In considering the strength of association of particular variables, we cannot ignore the effects of confounding factors that cause Simpson's paradox. Many methods for adjusting these effects have been proposed, and a great deal of effort has been devoted to statistical tests. Apart from the statisti
Al~traet--Two-way tabulation of data when a third interacting variable is present can lead to false inferences. In this paper it is shown that the probability of an occupant fatality given a crash in a single-vehicle accident is independent of vehicle size in an aggregate data set. When the data set