Bergsma, Wicher P.

Number of items: 32.
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  • Bergsma, Wicher, Lupparelli, Monia (2025). Editorial for special issue on categorical data analysis. Metrika, 88(6), 735 - 737. https://doi.org/10.1007/s00184-025-00999-z
  • Hagenaars, Jacques A., Bergsma, Wicher, Croon, Marcel (2019). Nonloglinear marginal latent class models. In Hancock, G. R., Harring, J. R. & Macready, G. B. (Eds.), Advances in Latent Class Analysis: A Festschrift in Honor of C. Mitchell Dayton (pp. 61 - 78). Information Age Publishing.
  • Bergsma, Wicher (2013). A bias-correction for Cramér’s and Tschuprow’s. Journal of the Korean Statistical Society, 42(3), 323-328. https://doi.org/10.1016/j.jkss.2012.10.002
  • Sejdinovic, Dino, Gretton, Arthur, Bergsma, Wicher (2013-12-05 - 2013-12-08) A kernel test for three-variable interactions [Paper]. NIPS 2013, Lake Tahoe, United States, USA.
  • Bergsma, Wicher, Croon, Marcel, van der Ark, L. Andries (2012). The empty set and zero likelihood problems in maximum empirical likelihood estimation. Electronic Journal of Statistics, 6, 2356-2361. https://doi.org/10.1214/12-EJS750
  • Ligtvoet, Rudy, Ark, L. Andries, Bergsma, Wicher P., Sijtsma, Klaas (2011). Polytomous latent scales for the investigation of the ordering of items. Psychometrika, 76(2), 200-216. https://doi.org/10.1007/s11336-010-9199-8
  • Rudas, Tamas, Bergsma, Wicher, Nemeth, Renáta (2010). Marginal log-linear parameterization of conditional independence models. Biometrika, 97(4), 1006-1012. https://doi.org/10.1093/biomet/asq037
  • Ark, L. Andries, Bergsma, Wicher P. (2010). A note on stochastic ordering of the latent trait using the sum of polytomous item scores. Psychometrika, 75(2), 272-279. https://doi.org/10.1007/s11336-010-9147-7
  • Bergsma, Wicher P, Croon, Marcel, Hagenaars, Jacques A. (2009). Marginal models for dependent, clustered, and longitudinal categorical data. Springer Berlin / Heidelberg.
  • Lupparelli, Monia, Marchetti, Giovanni M., Bergsma, Wicher (2009). Parameterizations and fitting of bi-directed graph models to categorical data. Scandinavian Journal of Statistics, 36(3), 559-576. https://doi.org/10.1111/j.1467-9469.2008.00638.x
  • Bergsma, Wicher, Croon, Marcel (2005). Analyzing categorical data by marginal models. In van der Ark, L. (Ed.), New Developments in Categorical Data Analysis for the Social and Behavioral Sciences (pp. 83-101). Psychology Press.
  • Rudas, Tamas, Bergsma, Wicher (2005). On applications of marginal models for categorical data. Metron, LXII, 1-25.
  • Bergsma, Wicher P, Rapcsak, Tamás (2005). An exact penalty method for smooth equality constrained optimization with application to maximum likelihood estimation. EURANDOM.
  • Galindo-Garre, Francisca, Vermunt, Jeroen K., Bergsma, Wicher P. (2004). Bayesian posterior estimation of logit parameters with small samples. Sociological Methods and Research, 33(1), 88-117. https://doi.org/10.1177/0049124104265997
  • Rudas, Tamas, Bergsma, Wicher (2004). Reconsidering the odds ratio as a measure of 2 x 2 association in a population. Statistics in Medicine, 22, 3445-3447.
  • Bergsma, Wicher P., Rudas, Tamas (2002). Marginal models for categorical data. Annals of Statistics, 30(1), 140-159. https://doi.org/10.1214/aos/1015362188
  • Bergsma, Wicher, Rudas, Tamas (2002). Modelling conditional and marginal association in contingency tables. Annales de la Faculté des Sciences de Toulouse, 11(4), 455-468. https://doi.org/10.5802/afst.1033
  • Bergsma, Wicher, Rudas, Tamas (2002). Variation independent parameterizations of multivariate categorical distributions. In Cuadras, C., Fortiana, J. & Rodriguez-Lallena, J. (Eds.), Distributions With Given Marginals and Statistical Modelling (pp. 21-28). Kluwer Academic Publishers.
  • Croon, Marcel, Bergsma, Wicher, Hagenaars, Jacques (2000). Analyzing change in categorical variables by generalized log-linear models. Sociological Methods and Research, 29(2), 195-229. https://doi.org/10.1177/0049124100029002002
  • Bergsma, Wicher P. (1997). Marginal models for categorical data. Tilburg University Press.
    • Public
  • Karch, Julian D., Perez-Alonso, Andres F., Bergsma, Wicher P. (2024). Beyond Pearson’s correlation: modern nonparametric independence tests for psychological research. Multivariate Behavioral Research, 59(5), 957 - 977. https://doi.org/10.1080/00273171.2024.2347960 picture_as_pdf
  • van der Ark, L. Andries, Bergsma, Wicher P., Koopman, Letty (2023). Maximum augmented empirical likelihood estimation of categorical marginal models for large sparse contingency tables. Psychometrika, 88(4), 1228 - 1248. https://doi.org/10.1007/s11336-023-09932-7 picture_as_pdf
  • Rudas, Tamás, Bergsma, Wicher (2023). Marginal models: an overview. In Kateri, M. & Moustaki, I. (Eds.), Trends and Challenges in Categorical Data Analysis: Statistical Modelling and Interpretation (pp. 67 - 115). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-31186-4_3 picture_as_pdf
  • Shi, Chengchun, Xu, Tianlin, Bergsma, Wicher, Li, Lexin (2021). Double generative adversarial networks for conditional independence testing. Journal of Machine Learning Research, picture_as_pdf
  • Bergsma, Wicher (2020). Regression with I-priors. Econometrics and Statistics, 14, 89 - 111. https://doi.org/10.1016/j.ecosta.2019.10.002 picture_as_pdf
  • Sankar, Subhra, Bergsma, Wicher, Dassios, Angelos (2017). Testing independence of covariates and errors in nonparametric regression. Scandinavian Journal of Statistics, 45(3), 421-443. https://doi.org/10.1111/sjos.12301
  • Gao, Wei, Bergsma, Wicher, Yao, Qiwei (2017). Estimation for dynamic and static panel probit models with large individual effects. Journal of Time Series Analysis, 38(2), 266-284. https://doi.org/10.1111/jtsa.12178
  • Dhar, Subhra Sankar, Dassios, Angelos, Bergsma, Wicher (2016). A study of the power and robustness of a new test for independence against contiguous alternatives. Electronic Journal of Statistics, 10(1), 330-351. https://doi.org/10.1214/16-EJS1107
  • Bergsma, Wicher, van der Ark, Andries (2015). Categorical marginal models: quite extensive package for the estimation of marginal models for categorical data. Comprehensive R Archive Network.
  • Bergsma, Wicher, Dassios, Angelos (2014). A consistent test of independence based on a sign covariance related to Kendall's tau. Bernoulli, 20(2), 1006-1028. https://doi.org/10.3150/13-BEJ514
  • Bergsma, Wicher P., Croon, M. A., Hagenaars, J. A. (2013). Advancements in marginal modeling for categorical data. Sociological Methodology, 43(1), 1-41. https://doi.org/10.1177/0081175013488999
  • Bergsma, W. P., Aris, E. M. D., Tibaldi, F. S. (2013). Linear Categorical Marginal Modeling of solicited symptoms in vaccine clinical trials. Statistics in Biopharmaceutical Research, 5(1), 27-37. https://doi.org/10.1080/10496491.2012.738111