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Communications in Statistics - Theory and Methods Volume 34, 2005 - Issue 8
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ANALYSIS OF CONTIGENCY TABLES

Catanova for Two-Way Contingency Tables with Ordinal Variables Using Orthogonal Polynomials

Luigi D'Ambra Department of Mathematics and Statistics, University “Federico II” of Naples, Naples, ItalyCorrespondence[email protected]
,
Eric J. Beh School of Quantitative Methods and Mathematical Sciences, University of Western Sydney, New South Wales, Australia
&
Pietro Amenta Department of Analysis of Economic and Social Systems, University of Sannio, Benevento, Italy
Pages 1755-1769 | Received 05 Sep 2004, Accepted 17 Feb 2005, Published online: 02 Sep 2006

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Antonello D'Ambra, Pietro Amenta & Anna Crisci. (2017) Decomposition of the main effects and interaction term by using orthogonal polynomials in multiple non symmetrical correspondence analysis. Communications in Statistics - Theory and Methods 46:20, pages 10179-10188.
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Christopher S. Withers & Saralees Nadarajah. (2017) Orthogonal polynomials generated by random vectors. Communications in Statistics - Theory and Methods 46:12, pages 6130-6136.
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Antonello D'Ambra. (2017) Cumulative correspondence analysis using orthogonal polynomials. Communications in Statistics - Theory and Methods 46:6, pages 2942-2954.
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Pasquale Sarnacchiaro, Antonello D’Ambra & Luigi D’Ambra. (2016) CATANOVA for ordinal variables using orthogonal polynomials with different scoring methods. Journal of Applied Statistics 43:13, pages 2490-2502.
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Antonello D'Ambra & Anna Crisci. (2014) The Confidence Ellipses in Decomposition Multiple Non Symmetric Correspondence Analysis. Communications in Statistics - Theory and Methods 43:6, pages 1209-1221.
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Luigi D'Ambra, Antonello D'Ambra & Pasquale Sarnacchiaro. (2012) Visualizing main effects and interaction in multiple non-symmetric correspondence analysis. Journal of Applied Statistics 39:10, pages 2165-2175.
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Rosaria Lombardo, Eric J. Beh & Antonello D'Ambra. (2011) Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials. Journal of Applied Statistics 38:10, pages 2119-2132.
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R. Lombardo & I. Camminatiello. (2010) CATANOVA for two-way cross classified categorical data. Statistics 44:1, pages 57-71.
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Biagio Simonetti, Eric J. Beh & Luigi D'Ambra. (2010) The analysis of dependence for three ways contingency tables with ordinal variables: A case study of patient satisfaction data. Journal of Applied Statistics 37:1, pages 91-103.
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Pasquale Sarnacchiaro & Antonello D’ambra. (2007) Explorative Data Analysis and CATANOVA for Ordinal Variables: An Integrated Approach. Journal of Applied Statistics 34:9, pages 1035-1050.
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Articles from other publishers (24)

Louis Laurencelle & Denis Cousineau. (2023) Analysis of frequency data: The ANOFA framework. The Quantitative Methods for Psychology 19:2, pages 173-193.
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Antonello D’Ambra, Giovanni Meccariello & Livia Della Ragione. (2022) Weighted cumulative correspondence analysis based on a particular cumulative power divergence family. Annals of Operations Research.
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Ida Camminatiello, Antonello D’Ambra & Luigi D’Ambra. (2021) The association in two-way ordinal contingency tables through global odds ratios. METRON 80:1, pages 9-22.
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Tamar Gadrich & Yariv N. Marmor. (2021) Two-way ORDANOVA: Analyzing ordinal variation in a cross-balanced design. Journal of Statistical Planning and Inference 215, pages 330-343.
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Inmaculada Barranco‐Chamorro & Christos Grentzelos. (2021) Some uses of orthogonal polynomials in statistical inference. Computational and Mathematical Methods 3:6.
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Luigi D’Ambra, Pietro Amenta & Antonello D’Ambra. 2018. Studies in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics 145 156 .
Rosaria Lombardo, Eric J. Beh & Pieter M. Kroonenberg. (2015) Modelling Trends in Ordered Correspondence Analysis Using Orthogonal Polynomials. Psychometrika 81:2, pages 325-349.
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. 2014. Correspondence Analysis. Correspondence Analysis 451 516 .
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Rosaria Lombardo. 2013. Data Mining. Data Mining 1472 1495 .
Rosaria Lombardo. (2011) Three-way association measure decompositions: The Delta index. Journal of Statistical Planning and Inference 141:5, pages 1789-1799.
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Ida Camminatie, Luigi D` Ambra, Giovanni Meccariell & Livia Della Ragione. (2011) A Study of Instantaneous Emissions through the Decomposition of Directional Measures for Three-way Contingency Tables with Ordered Categories. Journal of Applied Sciences 11:4, pages 693-699.
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Rosaria Lombardo. 2011. Surveillance Technologies and Early Warning Systems. Surveillance Technologies and Early Warning Systems 243 266 .
Rosaria Lombardo & Jacqueline J. Meulman. (2010) Multiple Correspondence Analysis via Polynomial Transformations of Ordered Categorical Variables. Journal of Classification 27:2, pages 191-210.
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Yoshio Takane & Sunho Jung. (2009) Tests of ignoring and eliminating in nonsymmetric correspondence analysis. Advances in Data Analysis and Classification 3:3, pages 315-340.
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Eric J. Beh & Thomas B. Farver. (2009) AN EVALUATION OF NON-ITERATIVE METHODS FOR ESTIMATING THE LINEAR-BY-LINEAR PARAMETER OF ORDINAL LOG-LINEAR MODELS. Australian & New Zealand Journal of Statistics 51:3, pages 335-352.
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Eric J. Beh & Luigi D’Ambra. (2009) Some Interpretative Tools for Non-Symmetrical Correspondence Analysis. Journal of Classification 26:1, pages 55-76.
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Eric J. Beh. (2008) Simple Correspondence Analysis of Nominal-Ordinal Contingency Tables. Journal of Applied Mathematics and Decision Sciences 2008, pages 1-17.
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R. Lombardo, E.J. Beh & L. D’Ambra. (2007) Non-symmetric correspondence analysis with ordinal variables using orthogonal polynomials. Computational Statistics & Data Analysis 52:1, pages 566-577.
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Eric J. Beh, Biagio Simonetti & Luigi D’Ambra. (2007) Partitioning a non-symmetric measure of association for three-way contingency tables. Journal of Multivariate Analysis 98:7, pages 1391-1411.
Crossref
Yves Escoufier. 2006. Compstat 2006 - Proceedings in Computational Statistics. Compstat 2006 - Proceedings in Computational Statistics 285 297 .
Luigi D’Ambra, Biagio Simonetti & Eric J. Beh. 2006. Compstat 2006 - Proceedings in Computational Statistics. Compstat 2006 - Proceedings in Computational Statistics 271 283 .

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