- Title
- On estimating the linear-by-linear parameter for ordinal log-linear models: a computational study
- Creator
- Beh, Eric J.; Farver, Thomas B.
- Relation
- ISRN Computational Mathematics
- Publisher Link
- http://dx.doi.org/10.5402/2012/340415
- Publisher
- Hindawi Publishing Corporation
- Resource Type
- journal article
- Date
- 2012
- Description
- Estimating linear-by-linear association has long been an important topic in the analysis of contingency tables. For ordinal variables, log-linear models may be used to detect the strength and magnitude of the association between such variables, and iterative procedures are traditionally used. Recently, studies have shown, by way of example, three non-iterative techniques can be used to quickly and accurately estimate the parameter. This paper provides a computational study of these procedures, and the results show that they are extremely accurate when compared with estimates obtained using Newton’s unidimensional method.
- Subject
- log-linear models; mathematical models; Newton; contingency tables
- Identifier
- http://hdl.handle.net/1959.13/1051985
- Identifier
- uon:15347
- Identifier
- ISSN:2090-7842
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Publisher version (open access) | 950 KB | Adobe Acrobat PDF | View Details Download |