Eric J. Beh

Personal Details

First Name:	Eric
Middle Name:	J.
Last Name:	Beh
Suffix:
RePEc Short-ID:	pbe172
	http://www.uws.edu.au/qmms/acadstaff/beh

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

1. Rosaria Lombardo & Eric Beh & Antonello D'Ambra, 2011. "Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2119-2132.

   Cited by:

   1. Eric J. Beh & Rosaria Lombardo, 2018. "An algebraic generalisation of some variants of simple correspondence analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 423-443, May.
   2. Ida Camminatiello & Antonello D’Ambra & Luigi D’Ambra, 2022. "The association in two-way ordinal contingency tables through global odds ratios," METRON, Springer;Sapienza Università di Roma, vol. 80(1), pages 9-22, April.

2. Irene L. Hudson & Linda Moore & Eric J. Beh & David G. Steel, 2010. "Ecological inference techniques: an empirical evaluation using data describing gender and voter turnout at New Zealand elections, 1893–1919," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 185-213, January.

   Cited by:

   1. Carolina Plescia & Lorenzo De Sio, 2018. "An evaluation of the performance and suitability of R × C methods for ecological inference with known true values," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 669-683, March.
   2. Jones, Daniel B. & Troesken, Werner & Walsh, Randall, 2017. "Political participation in a violent society: The impact of lynching on voter turnout in the post-Reconstruction South," Journal of Development Economics, Elsevier, vol. 129(C), pages 29-46.

3. Rosaria Lombardo & Eric Beh, 2010. "Simple and multiple correspondence analysis for ordinal-scale variables using orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2101-2116.

   Cited by:

   1. Rosaria Lombardo & Ida Camminatiello & Eric J. Beh, 2019. "Assessing Satisfaction with Public Transport Service by Ordered Multiple Correspondence Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 355-369, May.
   2. Rosaria Lombardo & Eric Beh & Antonello D'Ambra, 2011. "Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2119-2132.

4. Eric Beh & Luigi D’Ambra, 2009. "Some Interpretative Tools for Non-Symmetrical Correspondence Analysis," Journal of Classification, Springer;The Classification Society, vol. 26(1), pages 55-76, April.

   Cited by:

   1. Rosaria Lombardo & Eric Beh & Antonello D'Ambra, 2011. "Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2119-2132.

5. J. C. W. Rayner & Eric J. Beh, 2009. "Towards a better understanding of correlation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 324-333, August.

   Cited by:

   1. Lombardo, Rosaria & Camminatiello, Ida & D'Ambra, Antonello & Beh, Eric J., 2021. "Assessing the Italian tax courts system by weighted three-way log-ratio analysis," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).

6. Beh, Eric J. & Simonetti, Biagio & D'Ambra, Luigi, 2007. "Partitioning a non-symmetric measure of association for three-way contingency tables," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1391-1411, August.

   Cited by:

   1. Pardo, Julio A., 2010. "An approach to multiway contingency tables based on [phi]-divergence test statistics," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2305-2319, November.
   2. Rosaria Lombardo & Eric J. Beh & Luis Guerrero, 2019. "Analysis of three-way non-symmetrical association of food concepts in cross-cultural marketing," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2323-2337, September.

7. Lombardo, R. & Beh, E.J. & D'Ambra, L., 2007. "Non-symmetric correspondence analysis with ordinal variables using orthogonal polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 566-577, September.

   Cited by:

   1. Rosaria Lombardo & Jacqueline Meulman, 2010. "Multiple Correspondence Analysis via Polynomial Transformations of Ordered Categorical Variables," Journal of Classification, Springer;The Classification Society, vol. 27(2), pages 191-210, September.
   2. Pasquale Sarnacchiaro & Antonello D’Ambra & Luigi D’Ambra, 2016. "CATANOVA for ordinal variables using orthogonal polynomials with different scoring methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(13), pages 2490-2502, October.
   3. Blasius, J. & Greenacre, M. & Groenen, P.J.F. & van de Velden, M., 2009. "Special issue on correspondence analysis and related methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3103-3106, June.
   4. Eric J. Beh & Rosaria Lombardo, 2018. "An algebraic generalisation of some variants of simple correspondence analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 423-443, May.
   5. Antonello D’Ambra & Pietro Amenta, 2011. "Correspondence Analysis with Linear Constraints of Ordinal Cross-Classifications," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 70-92, April.
   6. Rosaria Lombardo & Eric Beh & Antonello D'Ambra, 2011. "Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2119-2132.

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