Some key papers and books by topic

Categorical Marginal Models:

Bergsma, W. P. and T. Rudas (2002). Marginal models for categorical data. Annals of Statistics, Vol. 30, 140-159. pdf.

Bergsma, W. P., M. A. Croon and J. A. Hagenaars (2009). Marginal models for dependent, clustered and longitudinal categorical data. Springer NY.

Rudas, T. and W. P. Bergsma and R. Nemeth (2010). Marginal log-linear parameterization of conditional independence models. Biometrika, vol 97, issue 4, pp.1006-1012 pdf

Bergsma, W., Croon, M., & J. A. Hagenaars (2013). Advancements in Marginal Modeling for Categorical Data (with discussion). Sociological Methodology. pdf

Measuring and testing of independence

Bergsma, W. P. and A. Dassios (2014). A test of independence based on a sign covariance related to Kendall's tau. Bernoulli, vol 20, issue 2, pp.1006-1028. pdf

Sejdinovic, D. and A. Gretton and W. Bergsma (2013). A kernel test for three-variable interaction. NIPS 2013. link

Publications

1. Bergsma, W. P. (1997). Marginal models for categorical data. Tilburg University Press: Tilburg.

2. Croon M. A., W. P. Bergsma, and J. A. Hagenaars (2000). Analyzing change in categorical variables by generalized log-linear models. Sociological Methods & Research. Vol. 29, No. 2, 195-229. pdf

3. Bergsma, W. P. and T. Rudas (2002). Marginal models for categorical data. Annals of Statistics, Vol. 30, 140-159. pdf

4. Bergsma, W. P. and T. Rudas (2002). Modeling conditional and marginal association in contingency tables. Annales de la Faculté des Sciences de Toulouse, Vol. XI, 2002, 455-468. pdf

5. Bergsma, W. P. and T. Rudas (2002). Variation independent parameterizations of multivariate categorical distributions. Pp. 21-28 in: Distributions with given marginals and related topics, eds. C. M. Cuadras, J. Fortiana and J. A. Rodriguez-Lallena. Kluwer Academic Publishers. pdf

6. Bergsma, W. P. and T. Rudas (2002). Restricting the marginals of contingency tables: potential problems and how they can be avoided. Metodoloski zvezki, Vol. 17, 75-86

7. Bergsma, W. P. and Croon, M. A. (2004). Analyzing categorical data by marginal models. Pp. 83-101 in: New developments in categorical data analysis for the social and behavioral sciences, eds. L. A. van der Ark, M. Croon and S. Sijtsma. Mahwah NJ: Erlbaum. pdf

8. Galindo-Garre, F., J. K. Vermunt and W. P. Bergsma (2004). Bayesian Posterior Estimation of Logit Parameters with Small Samples. Sociological Methods & Research, Vol. 33, No. 1, pp.88-117. pdf

9. Rudas, T. and W. P. Bergsma (2004). On applications of marginal models for categorical data. Metron, Vol. LXII, 1-25.

10. Wynn, H., T. Figarella, A. di Bucchianico, M. Jansen and W. Bergsma (2005). End of life analysis. Pp. 73-86 in: Modern Statistical Methods in Reliability, eds. Alyson Wilson, Nikolaos Limnion, Sallie Keller McNulty and Yvonne Armijo. World Scientific Publishing.

11. Bergsma, W. P., M. A. Croon and J. A. Hagenaars (2009). Marginal models for dependent, clustered and longitudinal categorical data. Springer NY.

12. Lupparelli, M., G. Marchetti and W. P. Bergsma (2009). Parameterizations and fitting of bi-directed graph models to categorical data. Scandinavian Journal of Statistics, 33, 559-576. pdf

13. Van der Ark, A. and W. P. Bergsma (2010). A note on stochastic ordering of the latent trait using
the sum of polytomous item scores. Psychometrika, Volume 75, Number 2, Pages 272-27. pdf

14. Rudas, T. and W. P. Bergsma and R. Nemeth (2010). Marginal log-linear parameterization of conditional independence models. Biometrika, vol 97, issue 4, pp.1006-1012 pdf

15. Rudy Ligtvoet, L. Andries van der Ark, Wicher P. Bergsma, and Klaas Sijtsma (2011). Polytomous latent scales for the investigation of the ordering of items. Psychometrika, 76, 200-216 pdf.

16. Wicher P. Bergsma, M. A. Croon, J. A. Hagenaars and L. Andries van der Ark (2012). Discussion of Probabilistic Index Models. J. Roy. Stat. Soc. B, 74, pdf.

17. Bergsma, W., Croon, M., & van der Ark, L. A. (2012). The empty set and zero likelihood problems in maximum empirical likelihood estimation. Electronic Journal of Statistics, 6, 2356-2361. pdf

18. Hagenaars, J. A. and W. P. Bergsma and M. A. Croon and (2013). Nonloglinear Marginal Latent Class Models. To appear in: Advances in Latent Class Analysis: a Festschrift in Honor of C. Mitchell Dayton. pdf

19. Bergsma, W. P., E. Aris and F. Tibaldi (2013). Linear Categorical Marginal Modeling of Solicited Symptoms in Vaccine Clinical Trials. Statistics in Biopharmaceutical Research, vol 5, p.27-37. pdf

20. Bergsma, W. P. (2013). A bias-correction for Cramer's V and Tschuprow's T. Journal of the Korean Statistical Society (in press). pdf

21. Bergsma, W., Croon, M., & J. A. Hagenaars (2013). Advancements in Marginal Modeling for Categorical Data (with discussion). Sociological Methodology. pdf

22. Sejdinovic, D. and A. Gretton and W. Bergsma (2013). A kernel test for three-variable interaction. NIPS 2013. link

23. Bergsma, W. P. and A. Dassios (2014). A test of independence based on a sign covariance related to Kendall's tau. Bernoulli, vol 20, issue 2, pp.1006-1028. pdf

Technical reports

• Bergsma, W. P. (2011). A note on the distribution of the partial correlation coefficient with nonparametrically estimated marginal regressions. pdf (arxiv)

• Bergsma, W. P. (2011). Nonparametric testing of conditional independence by means of the partial copula. pdf (arxiv)

• Bergsma, W. P. (2006). On a new correlation coefficient, its orthogonal decomposition, and associated tests of independence pdf

• Bergsma, W. P. (2004). Testing conditional independence for continuous random variables. EURANDOM-report 2004-049 pdf

• Bergsma, W. P. and T. Rapcsak (2004). An exact penalty method for smooth equality constrained optimization with application to maximum likelihood estimation. EURANDOM-report 2006-001 pdf

• Kulikov, V. and W. P. Bergsma (2004). Decoding aggregated profiles using dynamic calibration of machine vibration data. EURANDOM-report 2004-048 pdf

• Aris, E., W. P. Bergsma and Fabian Tibaldi (2012). Linear Categorical Marginal Modeling of Solicited
Symptoms in Vaccine Clinical Trials. Presentation given at the 33rd conference of the International Society for Clinical Biostatistics (Bergen, August 19th-23rd) pdf