![](/images/graphics-bg.png)
On Estimating the Linear-by-Linear Parameter for Ordinal Log-Linear Models : A Computational Study
Joint Authors
Source
ISRN Computational Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-28
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Beh, Eric J.& Farver, Thomas B.. 2012. On Estimating the Linear-by-Linear Parameter for Ordinal Log-Linear Models : A Computational Study. ISRN Computational Mathematics،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-464124
Modern Language Association (MLA)
Beh, Eric J.& Farver, Thomas B.. On Estimating the Linear-by-Linear Parameter for Ordinal Log-Linear Models : A Computational Study. ISRN Computational Mathematics No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-464124
American Medical Association (AMA)
Beh, Eric J.& Farver, Thomas B.. On Estimating the Linear-by-Linear Parameter for Ordinal Log-Linear Models : A Computational Study. ISRN Computational Mathematics. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-464124
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-464124