Computation of the quasi-independence model for the analysis of triangular contingency tables

2008 ◽  
Vol 89 (1) ◽  
pp. 72-75
Author(s):  
Serpil Aktaş
1987 ◽  
Vol 26 (03) ◽  
pp. 104-108
Author(s):  
M. A. A. Moussa

SummaryThe paper focuses upon the measurement of association in two-way contingency tables, using the log-linear models and dual scaling approaches. The former comprises [1] the use of pseudo-Bayes estimators to remove zeros, [2] fitting the resulting smoothed array to all possible configurations of log-linear models, [3] fitting the quasi-independence model to detect anomalous cells that caused deviation from the null-independence model. The latter includes [1] estimation of the optimal weights that maximize the canonical correlation between the two categorical variables by an optimization iterative method, [2] testing the discriminability of the estimated scoring scheme. The two approaches were applied to a set of real data for the study of the association between maternal age at marriage and types of reproductive wastage in a sampling survey conducted in the population of female nurses in Kuwait.


2018 ◽  
Vol 7 (3) ◽  
pp. 105
Author(s):  
Kiyotaka Iki ◽  
Shun Sato ◽  
Sadao Tomizawa

For two-way contingency tables with ordered categories, Tomizawa (1992) considered the parsimonious Linear-by-Linear association model. This model can be described in terms of fewer parameters than the Linear-by-Linear association model (Agresti, 1983). The purpose of this paper is (i) to define the parsimonious independence model, (ii) to show the parsimonious independence model holds if and only if the parsimonious Linear-by-Linear association model holds and the each one of various correlation coefficients is equal to zero, and (iii) show the statistic for testing the parsimonious independence model is asymptotically equivalent to the sum of test statistics for the decomposed models.


1993 ◽  
Vol 38 (8) ◽  
pp. 797-798
Author(s):  
Stephen E. Fienberg
Keyword(s):  

2016 ◽  
Author(s):  
Marek Kosny ◽  
Jacques Silber ◽  
Gaston Yalonetzky

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