- Title
- Adjustment to the aggregate association index to minimize the impact of large samples
- Creator
- Beh, Eric J.; Cheema, Salman A.; Tran, Duy; Hudson, Irene L.
- Relation
- Advances in Latent Variables: Methods, Models and Applications p. 241-251
- Relation
- Studies in Theoretical and Applied Statistics
- Publisher Link
- http://dx.doi.org/10.1007/10104_2014_24
- Publisher
- Springer
- Resource Type
- book chapter
- Date
- 2015
- Description
- The past few decades have seen a great deal of attention given to the development of techniques to analysis the association between aggregated categorical data. One of the most recent additions to this analysis has been the development of the aggregate association index (AAI). One feature of the AAI is that its magnitude is affected by the sample size; as the sample size increases so too does the AAI, even when the marginal proportions remain unchanged. In this article, we propose adjustments to the AAI to overcome the effect of increasing sample size. The Adjusted AAI is shown to be more stable than the original AAI in response to any increase in the sample size. Fisher's criminal twin data (Fisher, J. R. Stat. Assoc. Ser. A 98, 39-82, 1935) is used to demonstrate the adjustments.
- Subject
- aggregate association index; 2 x 2 tables; Pearson's chi-squared statistics; large samples
- Identifier
- http://hdl.handle.net/1959.13/1324592
- Identifier
- uon:25071
- Identifier
- ISBN:9783319029665
- Language
- eng
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